XXVII Brazilian Congress on Biomedical Engineering

Therapeutic ultrasound (TUS) is one of the most widely used methods for treating musculoskeletal injuries, in view of the benefits that this treatment provides: it speeds up the tissue repair process, for example. However, when TUS devices operate outside the range recommended by International Standard IEC 61689:2013, they can cause ineffective treatments or even aggravate the injury. This study aims to analyze the acoustic power emitted by a TUS device from Esquadrão de Saúde de Pirassununga and observe whether the values obtained are within the range established by the IEC 61689:2013. An acoustic radiation force balance was used to measure the power emitted by the equipment. The results showed that on all test days there was a divergence between the nominal and the emitted powers, which exceeded the value recommended by the IEC.

Previous studies have shown that cyclic imides and their subclasses have obtained positive results in biological activities, showing antimicrobial, analgesic and antifungal therapeutic potential. Arousing the interest of the scientific community and the pharmaceutical industry, surpassing expectations in relation to certain drugs used in the market. In this work we specifically perform the synthesis of one of the subclasses of cyclic imides, called maleimides, as they are easy to obtain and with good yields, in addition to being versatile for conjugation with other molecules. The synthesized compounds were identified by 1H and 13C nuclear magnetic resonance, mass spectroscopy and antibacterial activity was analyzed. In this work, a maleimide platform was obtained with different functional groups. These molecules showed synthesis yields (90%) and the activity was superior to the antibiotic streptomycin.

The aim of the present study is to investigate the therapeutic effect of wearing compressive socks composed of synthetic fibers with IR- emitting ceramic particulates on patients with edema of inferior member extremities. Thirty patients of both genders and age ranging from 30 to 70 years old (54.9 ± 13.3 years) were enrolled in the study and separated into two groups: C+ and placebo. The C+ group wore the compressive socks with embedded ceramic powder for at least 8 h a day for four weeks. The placebo group wore compressive socks made with fabrics of same material but without the ceramic particulate. The evolution of the treatment was assessed through plethysmographic measurements. The statistical analysis was done using the Kolmogorov–Smirnov normality test and a parametric two-tailed t-test with Welch correction at the significant level of α = 0.05. The Prism 8.0 software (GraphPad Software Inc., La Jolla, CA, USA) was used for the analysis. The experimental data showed a statistically significant reduction in edema volume for the ceramic-active group C+ , as compared to the placebo group. The treatment of leg edema using compressive socks containing ceramic particulate in its fabrics seemed to be more effective when compared with placebo socks.

This paper investigates the possibility of applying electric fields in different directions in a circular chamber using two insulated electrical pairs of electrodes positioned in orthogonal directions. Controlling the current on each axis—with two independent stimulator channels—we would be able to stimulate the central area in different direction according to superposition principle. This physical hypothesis is reasonable, and the work was focused on investigating if the resulting electric fields would be homogeneous in a small work area in a circular chamber. The electric field magnitude and orientation was determined with the measured electric potential data, and then the homogeneity tested with monofactorial ANOVA. A computational model was developed, based on the experimental setup, using finite element method to solve the electric field distribution within the chamber, in order to compare the experimental results. We tested the resulting electric field for theoretical orientations of 0 $$^{\circ }$$ ∘ and 31.7 $$^{\circ }$$ ∘ , and our results shows a electric field magnitude of 6.31 ± 0.11 V/m with p = 0.07 and 6.74 ± 0.40 V/m with p = 0.7032, and orientation of 0 $$^{\circ }$$ ∘ with p = 0.9997 and 31.7 $$^{\circ }$$ ∘ with p = 0.9999, respectively. Comparing the results with the analytical solution and the computational model, we observed that there was no statistical difference between them, which allows future biological experiment.

Regarding the cardiovascular system, in-vitro studies appears as an alternative for experimental assessment of blood flow parameters, in order to validating numerical simulation through particle imaging velocimetry (PIV) or laser Doppler velocimetry (LDV), and assist health professionals in clinical procedure. The aim of this study is to develop a methodology for manufacturing optical silicone models of blood vessels, life size, for the purposes described. A process similar to casting was used. A bipartite mold and a core were manufactured through of the 3D print after the geometry be acquired by computed tomography. The optical silicone was used to manufacture the model. After the cure of the silicone, it was observed that the model showed great transparency and compliance. This procedure showed up a simple and fast way for the manufacturing of optical silicone specimen of blood vessels. The results obtained were ideal for the purpose of the study, however the final model still lacks mechanical characterization for specific applications.

In numerical simulations of blood flow in the aorta, shear rates tend to be higher than 100 s $$^{-1}$$ - 1 , making blood behave as a Newtonian fluid, with constant dynamic viscosity. This study proposes a comparative analysis via computational fluid dynamics (CFD) of the Newtonian, Carreau-Yasuda, Power-Law and Casson rheological models for a realistic geometry of the aortic arch obtained by computed tomography (CT) and adapted with an aneurysm. It has been shown that there are instants of time throughout the cardiac cycle in which the blood exhibits non-Newtonian behavior. This behavior leads to a considerable variation in the dynamic viscosity that can influence the flow hemodynamics. It was also possible to detect that the effective viscosity varies over the cardiac cycle, including the Newtonian model, which suggests that the turbulent viscosity is variable. In general, the Carreau-Yasuda and Power-Law models show similar behavior, whereas the Casson model tends to be more closely to the Newtonian model.

Assessment of the mechanical ventilation in rodents is widely performed using a mechanical ventilator for small animals (SAV). One of the main adjustable parameters in SAV is tidal volume, typically 10 mL/kg, which is configured in relation with the animal body weight. Traditionally, the preset TLC maneuver is used for alveolar recruitment; this study aims to explore the data from TLC to screen the relative lung volume in Balb/c mice, in order to analyze its relationship to the body weight of mice. The TLC maneuver allowed us to measure the relative delivered lung volume from PEEP (positive end-expiratory pressure) to 30 cm H $$_{2}$$ 2 O. In overall, one hundred twenty-four (124) 13–20 week-old Balb/c mice were used, animals were split into two groups using mean value of the body weight (24g) as a cutoff point. Group H (n =51) had animals with body weight higher than the mean value, while mice with lower body weight belonged to group L (n = 73). Significant positive correlation was found within animals in the group H (r = 0.6137); conversely, animals in group L did not present correlation for relative volume and body weight ( $$r\approx 0$$ r ≈ 0 ). Additionally, an analysis of static compliance (Cstat) was conducted for each group using unpaired t-test ( $$p<0.05$$ p < 0.05 ). Therefore, it was possible to indicate that mice with lower body weight presented lower static compliance compared with those with greater body weight. Results suggest that tidal volume apparently depends on recruitment volume or compliance instead of the mice body weight.

Atrial fibrillation (AF) is the most common cardiac arrhythmia seen in the clinical practice, and treatments with antiarrhythmic drugs are of limited effectiveness. Radiofrequency catheter ablation (RFA) has been widely accepted as a strategy to treat AF. In this study, we analyzed the electrophysiological impact of different RFA strategies by varying the duration of ablation in a controlled protocol. The electrical activity of the isolated right atrium of rats, under different RFA time strategies, was acquired on the epicardium by electrical Mapping (EM), and simultaneously on the endocardium by Optical Mapping (OM). Analyses were performed in both time and frequency domain, through analysis of signal’s morphology, local activation time (LAT), conduction velocity (CV), dominant frequency (DF), and organization index (OI). The morphology of the optical and electrical signals with prolonged ablation time was altered as the ablation time increased. As observed, DF and OI decreased with the increase of the ablation time and resulted in fragmented electrograms. Through the characterization of traditional metrics applied to the electrical and optical data, it was possible to identify the important changes induced by the ablated area.

It is extremely important to check the morphological changes on the surfaces of the implants that will have an impact on their osseointegration and clinical longevity of the implant. For this reason, the purpose of this in vitro study was evaluated the damage caused to the surface of dental implants after different conditions of simulation of mechanical removal of the biofilm and scraping using several different protocols. There was no formation and removal of biofilm. Twenty-five implants of the Singular Implants® brand (Parnamirim, Brazil) were divided into 05 groups: G1 control- C (n = 5), G2 Ultrasound- US (n = 5), G3 Stainless Curette- INX (n = 5), G4 Teflon®-TF curtain (n = 5), G5 Laser-L (n = 5). Scraping was performed on the first three turns of the G2, 3 and 4 implants. The G5-L received irradiation with Laser Er:YAG (50 J, 1.5 W, 30 Hz). After the procedures, the implants were evaluated in SEM (1500–3000 X). It can be observed that in G4-TF there was no change in surface morphology and roughness, however residues of TF were deposited on the surface; in G3-INX important morphological changes were observed, with impression on the titanium of parallel striations typical of the use of curettes; in G5-L, flattening of the roughness peaks was observed, but not in the valleys; in G2-US several morphological changes were observed: total kneading of the roughness in some areas and fine scratches in others. It is concluded that of the protocols used, the least harmful to roughness was the laser, followed by stainless steel curettes and ultrasound. Teflon curettes did not change the surface roughness, but added material residues to the surface.

This article aims to evaluate the behavior of the arterial pressure response during alveolar recruitment maneuvers in spontaneously hypertensive rats (SHR). Such study can lead to a better understanding of arterial pressure behavior, which is relevant in the context of hypertension being a health condition. The animals were separated into groups: with and without Hydralazine treatment (20 mg/kg dissolved in drinking water) and two ages (17 weeks—2 weeks treatment and 21 weeks—6 weeks treatment). For the experiment, the animals were anesthetized, tracheostomized and connected to a small animal ventilator (flexiVent legacy, SCIREQ, Canada). The animals were connected to a custom-built arterial pressure monitor device. Arterial pressure and volume of the respiratory system were analyzed during two consecutive alveolar recruitment maneuvers. The results indicated that there is no statistically significant difference in arterial pressure during alveolar recruitment maneuvers, although respiratory system volume showed significant difference ( $$p < 0.0001$$ p < 0.0001 , ANOVA) among different groups. Regarding the percentage comparison between the period before ARM and the second ARM, there was statistical ( $$p< 0.0001$$ p < 0.0001 , ANOVA) difference in 17 weeks treated versus 21 weeks non-treated and 21 weeks treated versus ( $$p > 0.05$$ p > 0.05 for all). These findings could indicate that the drug, with the present dose and administration time, was not sufficient to decrease the basal pressure, however it influenced on the cardiovascular response during alveolar recruitment. Since there was no difference in the total air volume displacement in alveolar recruitment maneuvers among groups, the explanation to the influence on the cardiovascular response during alveolar recruitment is solely related with the cardiovascular system.

Biological or mechanical heart valve prostheses are used as a treatment to replace failing native heart valves. The goal of this study is to investigate the hydrodynamic performance of small sizes bileaflet mechanical heart valves (BMHVs) considering their use to control flow direction on a pulsatile pediatric ventricular assist device (VAD) [1]. Small size BMHVs of 17, 19 mm were tested in vitro and compared to 23 mm prosthesis. Each prosthesis was placed on a pulse duplicator (4–90 bpm, 2.0–4.0 L/min flow range) and pressure and flow signals were recorded to determine pressure gradient, flow regurgitation and effective orifice area (EOA). Pressure gradients (maximum/minimum; mmHg) were (12.2/8.5), (8.4/6.3) and (8.2/5.8), for 17, 19 and 23-mm, respectively. Valve effective orifice areas (maximum/minimum; cm2) were (1.05/1.02), (1.37/1.24) and (1.55/1.35) for 17, 19 and 23-mm sizes, respectively. The regurgitation fractions (maximum/minimum; %) obtained were (6.91/5.29), (10.47/6.08), and (14.63/10.04), for 17, 19 and 23-mm sizes, respectively. The results suggest that the mechanical valves have adequate performance according to the requirements of the ISO 5840:2015 standards and that they can be used to effectively control flow direction on a pediatric pulsatile ventricular assist device.

Despite the high success rate of dental prostheses in treating patients, mechanical failures still occur. Studies about the biomechanical behaviour of dental prostheses are thus important to avoid such failures and to ensure patient’s well-being. This study proposed a parametric and optimization analysis of a dental implant to investigate which implant’s structural parameters are more relevant to prevent failure and improve osseointegration. A mathematical function called response surface was obtained based on Von Misses stresses in the cortical bone, RSM (Response Surface Methodology), DOE (Design of Experiments), and finite element models. A structural optimization analysis was conducted with the objective of minimizing stresses in the cortical bone. In addition to the sensitivity analysis of the parameters, a more agile process to estimate critical stress through equations was presented, providing a faster way of identifying potential failure causes.

This study investigated the tribological behavior of the ASTM F138 austenitic stainless-steel – which is generally used in biomedical applications – treated with laser. Metallic biomaterial surfaces were treated under different nanosecond optical fiber ytterbium laser pulse frequencies, with the purpose to increase their surface hardness. Further, ball-cratering wear tests were conducted to analyze their tribological behavior on the basis of their wear volume and coefficient of friction. The obtained results showed that the nanosecond optical fiber ytterbium laser pulse frequency influenced the surface hardness of each specimen and, consequently, on the wear resistance of the ASTM F138 austenitic stainless-steel biomaterial. With an increase of laser pulse frequency, a decrease in the wear volume of the worn biomaterial was observed – which is the main tribological parameter to study the wear resistance of a metallic biomaterial. In contrast, the coefficient of friction values were found to be independent of the laser pulse frequency, surface hardness and the wear volume of the specimen.

This article presents experimental and computational results of electroporation in rabbit liver. Therefore, an empirical electroporation model was used, able to describe the dynamic behavior of electroporation. The experiments were perform with a cylindrical electrode system, where voltage pulses with three different levels were applied. For the numerical simulation of electroporation, a finite element software in MatLab $$^\text{\textregistered }$$ ® was developed, intended for academic research. The electroporation model combined with the Finite Element Method proved to be an appropriate simulation tool for the study of biological electropermeabilization.

Acute rupture of the calcaneus tendon is relatively common, usually related to sports practice. In recent years, the number of researches in search of more efficient techniques, which induce the healing process, has been growing. The Fibrin Sealant Derived from Snake Venom (FSDSV) or Heterologous Sealant has been standing out in animal and human application for accelerating the repair of lesions, reducing the likelihood of hemorrhage and infectious diseases and having low production cost. Aquatic exercise also presents itself as an efficient strategy for rehabilitation, reducing pain and edemas, improving muscle properties and enhancing the repair process due to the numerous beneficial effects provided by the liquid medium. The aim of this research is to evaluate the use of fibrin sealant derived from snake venom associated with aquatic exercise in tendon repair. We used 84 rats of the Wistar strain, weighing between 170 and 250 g of weight who underwent surgery to induce partial rupture of the calcaneus tendon. The animals were randomly separated into four experimental groups. The technique used was the application of fibrin sealant and aquatic exercises according to the studied group. There was a greater reduction in the edema of the animals’ paws from the seventh day on in all treatments (p < 0.002), when compared to the control group. After 7 and 14 days of treatment, LE showed a greater reduction in the volume of edema (p = 0.03041) compared to the control. After 21 days, the (LS) showed a greater reduction in edema compared to the control group. It was possible to verify a higher collagen to LSE ratio in the evaluated period after 21 days of treatment. Thus, the heterologous fibrin sealant associated or not with aquatic exercise has a beneficial influence on tendon repair, becoming a propitious technique for future clinical applications.

The mitral valve (MV) along with the tricuspid valve are part of the atriovalvar complex and, when committed by myxomatous disease, suffers from tissue degeneration with severs changes in its mechanical properties, consequently loosing its coaptation capability, resulting in the well known Mitral Regurgitation (MR). This paper presents the results of stress $$\times $$ × strain tests of 19 mitral valve posterior leaflets committed by myxomatous disease extracted from patients undergoing MV repair surgery. Due to their dimensions, only uni axial testes were performed, i.e., only the radial direction was considered. Are presented the Young Modulus, Yielding and Linearity limits. The Young Modulus obtained for myxomatous MV are compared to normal values found in the literature.

The aim of this study was to investigate the printability of different compositions of biomaterials to be potentially used in bioprinting of cartilaginous substitutes. Part of the compositions contained pulverized devitalized cartilage (DVC), which confers the necessary biochemical complexity for bioprinted scaffolds, and some compositions contained granulated polycaprolactone (PCL), that provides greater mechanical resistance to the scaffolds. An additive manufacturing equipment specially customized for bioprinting was used in the printing tests. In addition to bringing biochemical advantages, DVC increases consistency of scaffolds. PCL, on the other hand, has to be reduced to smaller granulometries for better results, since it has obstructed the printing needles. Modifications to the printer design have been suggested to make printing viable using high viscosity biomaterials and 0.41 mm or thinner needles, which may provide greater resolution and shorter distances for diffusion of nutrients and oxygen inside the scaffolds.

This research aimed to perform chemical synthesis using the B-complex to obtain similar conductive and magnetic characteristics to the Polypyrrole polymer, which presents biocompatible properties. The technique, characterized as low-cost, can be used in many applications, since as biomaterials in biomedical area until telecommunications area. To obtain the Polypyrrole, it was chosen two methods and four treatments to achieve the powder. The conductive properties of the resulting powders were verified using the four-probe technique to measure the voltage; the conductivity was performed using a conductivity meter, and the HD magnet was used to check the magnetic properties of the synthesized powder. The results obtained for the conductivity was ≈ 1.68 µS/cm, and the voltage was about 1.31 mV. The use of B-complex as a substitute of the Polypyrrole shows similar results to its conductive characteristics, been a viable alternative as biomaterial application.

Cancer is one of the diseases with the highest incidence in the world and that associated with the patient's emotional state, can act positively or negatively in the treatment. Cortisol is described as a primary stress hormone in the human body. Studies show a positive correlation of elevated cortisol levels and cancer progression. The corticoids can increase cell proliferation and increased reactive oxygen species that contribute to DNA damage. Prolonged exposure to stress can contribute to tissues becoming insensitive to cortisol, the primary human stress hormone. This study explores the influence of cortisol, an important hormone involved in stress, on tumor cell development, particularly in human cells of carcinoma of human laryngeal (HEp-2). HEp-2 cells were exposed to increasing cortisol (hydrocortisone) concentrations for 24 or 48 h and cytotoxicity (MTT assay [3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazio bromide], proliferation assay (crystal violet assay), and immunolabeled 3D culture for fibronectin and FAK were investigated. Corticosteroids and stress in cancer patients may inter-fere with cancer treatments because these may cause tumor cells to progress instead of reduce depending on the cell type. Although some cases favored corticosteroids use in cancer patients, a more detailed analysis is necessary be-fore prescribing them. Moreover, it is important to assess the patient’s cortisol level before and after treatment as well.

The use of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) to replace myocardial tissue after an infarct holds great promises. However, hiPSC-CM are phenotypically immature when compared to cells in the adult heart, hampering their clinical application. We aimed to develop and test a surface structuring technique that would improve hiPSC-CM structural maturation. Laser ablation was used to fabricate a micron-pattern on polyurethane surface and evaluated cell morphology, orientation and F-actin assemblage to detect phenotypic changes in response to the microtopography. This topography positively influenced cell morphology regarding to spreading area and elongation, and hiPSC-CM orientation, improving their structural maturation. The methodology thus presented has relatively low cost and is easily scalable, making it relevant for high-throughput applications such as drug screening for the pharma industry.

This study investigates the effect of the nitrided layer on antibacterial properties of biomedical stainless steel, grade 316L. The surfaces were sanded #1200 mesh papers, subsequently plasma-nitrided at a temperature of 400 °C for 2 h, which resulted in a 4.5 μm thick layer. The characterization was made using optical and scanning electron (SEM) microscopies, energy dispersive spectrometry (EDS) X-ray diffraction, and Vickers hardness testing. The antibacterial characteristic of the untreated steel and the nitrided layer was evaluated using Gram-negative Escherichia coli ATCC8739, according to Japanese International Standard (JIS) no. Z2801:2000. A single γ-phase layer was formed, supersaturated in nitrogen, increasing the surface hardness significantly by 35%. The bacterial test demonstrated that the nitrided layer presented suitable antibacterial characteristics.

The chondral lesion and osteoarthritis are conditions associated with an economic burden, since if left untreated may cause changes in the biomechanics of the joint and result in several injuries considered highly disabling to the individual. Mesenchymal Stem Cells (MSCs) have the immunomodulatory capacity and paracrine signaling that are useful for tissue bioengineering to treat bone and cartilage injuries. To the best of our knowledge, there is no institution in Brazil studying cartilage biomechanical properties in Good Manufacturing Practice (GMP) technique. Therefore, this study aims to describe biomechanics analysis for cartilage restoration by tissue engineering and cell therapy treatments in a GMP translational large animal model. A controlled experimental study in fourteen Brazilian miniature pigs was performed, using scaffold-free Tissue Engineering Construct (TEC) from dental pulp and synovial MSCs with 6 months follow-up. To compare the cartilage with and without TEC, indentation and maximum compressive tests were performed, as well as Finite Element model to simulate the osteochondral block and characterize its properties. The Young’s Modulus of each sample was determined, and the outcomes of maximum compressive test demonstrated the cartilage integrity. The proposed method was feasible and capable to properly evaluate articular cartilage restoration.

Nitric oxide (NO) is a small diatomic molecule, endogenously produced, and plays important roles in many vital biological processes including angiogenesis, antioxidant/antitumor/antimicrobial actions and tissues regeneration such as skin, cartilage and bone. For being a free radical, NO is relatively instable in biologic system and it can be rapidly inactivated. Among then, the S-nitrosothiols (RSNOs) are prominent, which spontaneously decompose releasing NO. The combination of RSNOs and biomaterials represent a promising strategy to increase the therapeutic efficiency of these NO donors. In this way, the main objective of this study was to evaluated cytotoxicity of thermosensitive poloxamer/hyaluronic acid hydrogels (PL/HA) and chitosan nanoparticles (CS NPs) containing NO donors (RSNOs), using the kidney cells of African green monkey (Vero). The results obtained by quantitative MTT assays showed cell viability dependent on the concentrations of SNAC and polymeric biomaterials. Thus, these results point the in vitro biocompatibility of PL/HA and CS NPs systems containing NO donors and their possible application in bone tissue regeneration and also contribute to studies using Vero cells.

Polymeric biomaterials are used in tissue repair due to characteristics as biocompatibility and cell interaction. In the category of synthetic polymers, poly lactic acid (PLA) is especially used in several clinical applications. This biomaterial can be prepared in the form of dense and porous membranes, in order to characterize the interaction with Vero cells in culture, using scanning electron microscopy (SEM). For this purpose, dense and porous PLA membranes were previously prepared, sterilized by ultraviolet light (UV) and used as a substrate for cultivation of Vero cells, for periods of 2 h and 7 days. To observe the cell interaction with the membranes, different methodologies for processing the samples for observation by SEM were considered, and a comparative analysis of the results was performed. There was no significant difference in cell morphology comparing samples with and without osmium tetroxide, however samples that underwent drying at a critical point had better preservation of cell morphology compared to samples in chemical drying. Osmium tetroxide is not a major factor in the processing of cells for SEM, and that the type of drying is the factor that most affects cell morphology in this process. It was possible to observe cell adhesion after 2 h of culture, with morphological changes such as cytoplasmic transition to a more flat aspect being more characteristic for 7 days of culture.

Myocardial Tissue Engineering (MTE) is a set of techniques that uses biomaterials to reproduce the native extracellular matrix (ECM) of tissues, in this case, the myocardium. The present contribution relates the results of the study about the electrospinning of gelatin, a naturally occurring biopolymer, in view to obtain nanofibrous scaffolds for use in MTE. Gelatin solutions were prepared using gelatin type B and 2,2,2-Trifluoroethanol (TFE) as a solvent. The fibrous were created through electrospinning technique. The voltage, distance and concentration of the solutions were varied to improve the quality of the fibers. The crosslinking method was validated with the use of films, prepared by solvent evaporation technique, with 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC). The morphology of the fibers was investigated by scanning electron microscope (SEM) and the efficiency of the crosslinking processes were evaluated by swelling test and differential scanning calorimetry (DSC). The best fibers were formed (without the presence of drops or beads) by electrospinning a gelatin solution in the following parameters (10% (w/v), 10 kV and 20 cm) or (5% (w/v), 12 kV and 12 cm). The crosslinking process was done using EDC in the films of gelatin. It was possible to observe that different degrees of crosslinking guarantee different properties, such as water swelling as well as different thermal and mechanical properties.

Mechanical circulatory assistance with left ventricle assist devices (VADs) can be used for hemodynamic stabilization in patients waiting for heart transplantation. In this application the VAD is connected to the heart with the use of special cannulas. The purpose of this work is to present in the performance of long-term cannulas designed for pediatric patients undergoing circulatory assistance. Pressure drop of cannulas with different sizes were tested using a mock loop of the pediatric arterial circulation. Considering a flow range of 0.52–1.25 L/min the pressure drops obtained was 9.43 to 22.1 mm Hg, respectively. Good clinical results were obtained with cannulas associated with a centrifugal pump or DAV for a period of approximately 4–64 days, with no thrombus formation on the tips of the cannulas or bleeding. The implantation of cannulas proved to be technically feasible and their removal was easy to perform in cases of ventricular recovery or transition to a long-term assistance device.

Phytotherapy can have several applications, such as anti-inflammatory, analgesic, antinociceptive, antimicrobial, antiviral and tissue regeneration. It is important to characterize the effects of these drugs to verify clinical safety, avoiding possible adverse reactions, like toxicity, digestive discomfort and headache. In this research, the effects of total aqueous and ethanolic extract of Lantana trifolia L was analyzed on Vero cell cultures, seeking to understand how the cellular response to different concentrations (25, 50, 75 and 100 µl/ml) of the extracts. There were carried out quantitative and qualitative, morphological evaluation, of the cultured cells in the presence of the extracts. The quantitative results showed cell viability dependent on the concentration of test extract. The cellular viability remained above 70%, therefore for all experimental conditions, resulting in non-cytotoxic effects, both for aqueous and ethanolic extracts. With the statistical analysis of the results obtained it was possible to conclude that there was no significant variation in cell viability, that is, although the extract is non-cytotoxic, it does not cause cell proliferation in the medium. The quantitative results are in accordance with the qualitative analyzes.

Currently, look for alternative healing membranes that can perform actions such as safe and secure physical barrier, allowing proper gas exchange, being clinically effective, easy to apply, manipulating and assisting in wound care. Face this need, demonstration or potential of bull skin for use as a healing membrane, being used in this work antibiotic for skin disinfection. O ozone (O3) is known for its high antimicrobial effect without development of resistant tissue. The present work had standardized disinfection performance using ozone and the bull skin membrane lifetime test. Opened in February 2019 and after verified microbiological test-if there was no contamination. Through the preliminary results of the useful life test, the next steps of the study to evaluate dressings in animal model were determined.

Marking is one of the last steps of manufacturing an implantable biomaterial. The marks on its surface constitute a permanent set of information in order to provide identification and traceability of the biomedical device. These markings become stress concentrators and regions with probability for the occurrence of failures that can lead to fracture; besides damaging the passive layer, naturally formed on stainless steels surfaces, favoring the beginning of several forms of degradation. This work presents the effect of two metal implant marking techniques on the corrosion resistance of ISO 5832-1 austenitic stainless steel, one of the most used surgical biomaterials used in Brazil. Engraving was carried out with mechanical and laser beam marking techniques were prepared. The electrochemical behavior was characterized by cyclic potentiodynamic polarization curves and indicate that the laser marking technique is the one that most affects the passive layer of the material when compared to the mechanical engraving.

Electrospinning has been widely applied to obtain nanofiber based biomaterials to be used as scaffolds in tissue engineering. The aim of this work is to obtain and characterize membranes of a composite material obtained by electrospinning of Poly(ε-caprolactone) (PCL) combined with reduced graphene oxide (rGO) 0.05% (PCLrGO005) and 0.5% (PCLrGO05) concentrations. Besides rGO concentration, the influence of electrospinning parameters was investigated (PCLrGO005M). The mechanical behavior of the new materials was studied considering the mechanical tensile test according to the ASTM D638 standard. Surface qualitative analysis was done by measuring fiber diameter using scanning microscopy. Four different membranes were obtained by random electrospinning using two needles and 5 mL volume solution at 18 kV, 15 cm needle distance and 0.033 mL/min flow rate or modified parameters of 15 kV, 10 cm needle distance and 0.012 mL/min flow rate. The modulus of elasticity, maximum load, tensile stress and strain were obtained for all membranes and analyzed by ANOVA. The morphological surface analysis of the scaffolds showed that the nanomaterial scaffolds of PCL and rGO with good mechanical properties and uniform surface morphology can be obtained by careful adjustments of electrospinning process parameters.

In this work, we developed and tested an experimental apparatus to evaluate calcium fluctuations in cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CM). The set-up is composed of a signal module for registration and analysis of the signals and a perfusion chamber. This chamber allows the maintenance of the cells, control of perfusion and temperature, and electric stimulation. The signal module consists of a CCD camera attached to a fluorescence microscope with the appropriate software and hardware for eliciting and recording fluorescent signals originating from hiPSC-CM intracellular Ca+2 concentration changes, under electrical stimulation. We employed this system for analysis of calcium fluctuation from hiPSC-CM cultivated on micro textured polyethylene terephthalate surfaces.

Tissue Engineering involves the proposal for tissue repair using biomaterials: materials used in biomedical applications in order to regenerate tissues or restore their functions. To verify the viability of biomaterials, one must consider their biological performance, that is, their interaction with the organism, including properties related to biofunctionality and biocompatibility. Initial biocompatibility tests are carried out with cytotoxicity evaluation. However, although the test conditions for cytotoxicity tests are standardized, some studies present divergent data regarding the cytotoxicity of biomaterials. Sample preparation conditions and test conditions can directly affect the results. The objective of the present work is to evaluate different cytotoxicity conditions of alumina (Al2O3) and calcium hexaluminate (CA6) samples as a function of the variables: sample washing conditions, sample size and total test time. The biomaterial samples were positioned on a Vero cell confluent monolayer. In order to verify cell morphology, it was used inverted microscopy with phase contrast. The results indicate that both alumina and washed alumina are viable and non-cytotoxic. The hexaluminate presented slight cytotoxicity, in different experimental conditions.

Phantom mimics biological tissues properties, i.e., acoustic and mechanical. Tendon connects muscle to bone and allows joint motion. To evaluate tendon mechanical properties, i.e. Young modulus, in vitro and in vivo studies were developed. In the 90s, Elastography emerged as a promise tool to tissue mechanical properties assessment, i.e., breast and liver. Recently, Supersonic Shear Imaging (SSI) technique was developed to calculate quantitative Elastic modulus (E) from transversal shear wave propagation velocity (CS). The most recent 3D transducer can provide a tridimensional visualization of an organ (sagittal, transverse and coronal). The aim of this study is to assess transverse shear wave propagation velocity (CS) on tendon phantom using SSI with 3D transducer. This tendon phantom was composed basically PVCP plastisol® and glycerin (15%). For image acquisition, the Aixplorer v.11 equipment (Supersonic Imagine, Aix-en-Provence, France) with 3D transducer (Super linear TM volumetric SLV 16–5, 5–16 MHz) were used. The 3D transducer was placed randomly at the phantom surface and three images were acquired. Each one presented the three orthogonal planes (sagittal, transverse and coronal) and the respective intersection points between two other planes. For each plane, a 5.0 mm ROI (Region of Interest) was positioned around the intersection point to measure CS. The mean CS values were 6.2 m/s (+0.3), 6.4 m/s (+0.4) and 6.3 m/s (+0.3) for sagittal, transverse and coronal planes, respectively. These results were different to the only study which evaluated an anisotropic phantom tendon with SSI. However, when compared to previous studies, the results were similar to human healthy patellar tendon. This is a whole homogeneous phantom and it was not possible to mimic the oriented fibers presented on the tendon. Future studies should be performed with anisotropic phantoms to standardize the validation of elastography techniques dedicated to healthy and pathological tissues.

Several control strategies have been proposed to achieve physiological adaptation of ventricular assist devices (VADs). This paper presents physiological control systems for pediatric VADs that were developed in a scientific cooperation between Bioengineering Division of the Heart Institute, Hospital das Clínicas, Faculty of Medicine on the University of São Paulo (InCor–HCFMUSP) and the Electrical Engineering Department at the Federal University of Campina Grande (DEE - UFCG). The pumping principle and mathematical models of two types of pediatric VADs (pulsatile and rotary) are described. The control strategies for the physiological control systems are discussed, and the main achievements and challenges for implementing these control systems are presented.

In recent years, calcium phosphate ceramics have been explored also as injectable materials for bone repair, due to their advantageous properties including moldability, biocompatibility, bioactivity and osteoconduction. Therefore, new formulations have been developed for calcium phosphate cements (CPCs) as injectable ceramics enable minimally invasive application. In the present study, a calcium phosphate cement with and without collagen in its composition was prepared and their characteristics evaluated. A solution of phosphoric acid (3.0 M) as liquid phase was mixed with the β-tricalcium phosphate, at a powder/liquid of 1:1 (wt%) ratio. An amount of 20 wt% collagen was added to the CPC and pH, temperature and setting times were monitored. Cements were characterized by XRD, FTIR, apparent porosity and SEM, in addition to mechanical behavior by elastic modulus analyses. The 20 wt% collagen amount showed suitable setting time. Monetite was the major phase in cement, as result of the methodology used. The presence of collagen covered the calcium phosphate particles, influencing in the setting time, dissolution reaction and formation of other phases in the cement, in addition to preserving a residual amount of the precursor ceramic phase. The collagen also decreased the apparent porosity, due to the coverage of the dicalcium phosphate crystals, allowing the filled of the microporosity. The elastic modulus values obtained were similar to those reported in the literature. The addition of collagen altered its mechanical performance to elastic modulus values between the cortical and trabecular bone range.

Congestive Heart Failure is a cardiovascular disease with global incidence and high mortality. In advanced stages, when patients are already refractory to drug therapies, there are two main alternatives, the heart transplantation, or the mechanical circulatory support. Ventricular Assist Devices are blood pumps designed to circulate blood in physiological conditions. Thus, hemolysis prediction is indispensable in VAD development. In literature, there are several models based on scalar stress analysis for estimating hemolysis index. Here, a different kind of analysis based on stress distribution and critical stress is proposed. Simulations were performed in a VAD prototype and 5 turbulence models were tested. Results show the distribution of scalar stress magnitudes according to their volume distribution and an important discussion and qualitative analyses were made, despite overall scalar stress measurements which generalize the results.

Since its beginning, artificial intelligence (AI) had as a strategy to mimic human cognition. In the area of physical rehabilitation, studies include AI to process, estimate and classify the level of physical activity to improve professional-patient relationship. This work aimed at developing and comparing Sugeno (FLS) and Mamdani (FLM) Fuzzy Logic (FL) implementations. These implementations have as main objective to assist the physiotherapist in making a decision to allow the patient to return to daily activities safely and in the shortest possible time. The implemented systems are composed of fuzzy rules (if—then) and four inputs of a range of motion, extension and flexion; pain intensity; and muscle strength; to generate an output on the physical capability of the knee. The qualitative requirements of the systems took into account the processing time, precision, and reliability of the responses. Practical results suggest that Sugeno’s method is the one more reliable regarding the level of membership function. However, both systems agreed on the values reported in six hypothetical clinical cases and the resulting capability concepts. The experiment consisted of three physical therapists, who responded to the same six clinical cases and their responses were compared with the conceptual outputs of the FLM and FLS systems. The level of agreement was high in two of the six cases and low in the other four. It is believed that if a larger number of professionals has access to this innovative method of assessment in the rehabilitation area, the higher agreement level may be reached. With this pupose, several clinical tests can be added as training inputs in order to improve the proposed method.

Stroke is a leading cause of disability in the world. It may leave several sequels such as the reduction of the function of the upper limbs, which directly affects the performance of activities of daily living. This dysfunction can be closely linked to the spasticity and the decrease in range of motion, impacting the quality of life of these patients. In this sense, a training protocol was applied involving a serious game based on virtual reality (VR), in order to facilitate the return of the neurological motor function. This treatment was applied on the two upper limbs of an individual who had a stroke in both sides of the brain. Fifteen treatment sessions were applied and the individual was evaluated in the first and last session. The evaluated parameters were: Modified Ashworth Scale (MAS), Range of Motion (ROM), Tonic Stretch Reflex Threshold (TSRT) and Quality of Life (QoL). It was possible to observe that, the offered protocol was able to reach the objective, since the presented results indicated an improvement in the parameters evaluated in the research. Emphasizing that the game scenario and the applied protocol helped in the involvement and improvement of the participant.

The measurement of joint angles is an important indicator of its functional state and for clinical diagnoses. Joint angle assessment techniques can be applied to improve sports performance and provide treatment and rehabilitation information. Recently, several sensors have been designed to detect movements of the human body. In this sense, a systematic review was carried out based on studies from the period of 2014 to 2019. The sources of research were the following databases: Capes Journals, IEEE Xplore and PubMed, in which 44 publications related to technologies applied for elbow joint angle measurements were selected. Eleven measurement methods were identified, the most used was: IMU sensors, mobile apps and fiber optic sensors. The results show that it is an area in constant expansion, with most of the papers published in recent years and with great potential for development and applications. The benefits of research can go far beyond indicating the sensors most used in the literature, but provide the most suitable for each application. In addition to facilitating the standardization of assessment methods for use in clinical practice. It is worth mentioning that the literature review has identified the main gaps for the development of new research, in addition to direct the main publications related to the study.

Disability covers countless people around the world, affecting in many and different ways. The inclusion of assistive technology (AT) aims to provide greater independence, expanding users’ mobility, communication and learning. Among some assistive technologies, we can mention the wheelchair. With the advancement of technology, different models of chairs have been developed aiming at the independence of people with disabilities and, currently, most users choose the motorized wheelchair (CRM). Although widely used, many users do not receive training before starting continuous use, which generates fear and frustration. The training can bring confidence and help the user to overcome several challenges, which focus not only on the use of assistive technology, but also on the acceptance of the disability. For a better understanding of how the inter-action between the user and assistive technology takes place, a questionnaire was elaborated addressing aspects such as personal characterization, characterization of the disability and evaluation of CRM and training. The survey was conducted between July and August 2019 and included 91 participants. With the results obtained, we can see which types of disabilities use the wheelchair the most, how long they use it, whether there was training, whether there are fears and obstacles to be overcome even with the constant use of the wheelchair, among other issues. Given these answers, it is possible to confirm a real demand for training before using a motorized wheelchair, since this practice would bring numerous benefits to the user.

A kinematic approach for a 4 degree-of-freedom (DoF) upper-limb robotic exoskeleton is presented in this study. The aim is to reproduce simple sequence of movements frequently performed in daily activities, such as shoulder flexion/extension and adduction/abduction, arm internal/external rotation, elbow flexion/extension and wrist pronation/supination. The kinematic model obtained through an analytical approach is presented. Simulations of several rehabilitation tasks performed by our exoskeleton show that this approach is able to carry out complex movements in the articular and Cartesian spaces with view of future implementation, using point-to-point, coordinated and continuous trajectories.

This work proposes an integrated method to analyze, from a kinetic and a clinical perspective, the degenerative condition of the mechanical properties of the femur due to the bone density decrease in patients with transfemoral amputation. A dynamic study of gait was conducted in order to obtain the kinematic and the kinetic variables from both limbs, which then were integrated into a finite element (FE) model of the socket-femur-residual limb system and the intact leg. Such models employed computed tomography (CT) scans of the amputated and the intact leg of all the volunteers for this study. Mechanical properties like the apparent density of the trabecular part and the cortical part of the bone of both legs were determined, as well as the Young’s modulus and the tensile yield strength. All these physical and mechanical properties were based on indexes extracted from CT scans, expressed in the Hounsfield (HU) scale. These results may help in investigating correlations to the degenerative condition of the mechanical properties with the bone density alterations and then to establish the possibility of fractures occurrence in the hip joint at different activity levels of the amputee patients.

The aim of the present study was to investigate the potential of the forced oscillation technique (FOT) in the evaluation of the respiratory mechanics of patients with scoliosis and its association with physical performance. A total of 41 subjects was analyzed, 24 with scoliosis and 17 controls. The distance covered in the six-minute walk test (6mWTd) was used to evaluate the physical performance. Scoliosis caused a significant increase in mean resistance (p = 0.05), resonant frequency (p < 0.05), and a significant reduction in mean reactance (p < 0.01), dynamic compliance (p < 0.05) and 6mWTd (p < 0.0001). A significant and inverse correlation was observed among resonant frequency (R = −0.49, p < 0.02) and mean reactance (R = −0.44, p < 0.03) with the 6mWTd. These data are consistent with previously published results and physiological fundamentals, confirming the high potential of the FOT in the assessment of the respiratory abnormalities in patients with scoliosis. The use of FOT may help in the evaluation of pulmonary function in scoliosis, contributing also to increase our pathophysiological understanding of the respiratory abnormalities in these patients.

Chronic obstructive pulmonary disease (COPD) includes emphysema and chronic bronchitis. These different phenotypes may introduce different characteristics that need to be known to improve COPD treatment. Thus, the objective of this study is to identify through the forced oscillations technique (FOT) the differences in respiratory mechanics in these phenotypes before and after bronchodilator (BD) use. In this cross-sectional study, the results of a sample of 30 volunteers are presented, being divided into control group (CG = 10), emphysema (ENF = 10) and chronic bronchitis (CB = 10). Spirometric and plethysmographic exams were also performed. Before BD, resistances were higher in CB than in controls, a fact that did not occur in a similar comparison in patients with ENF. It were observed increased resistances and impedance modulus in CB in comparison with ENF after BD use, which may be explained by secretion mobilization due to maximum expiratory effort during spirometry. These results provide evidence that the presence of CB results in greater respiratory work than that resulting from the presence of ENF. This new information on COPD phenotypes can contribute to improving the therapeutic strategies used, and consequently, to the assistance offered to these patients. The presented results also provide evidence that FOT is a useful tool in evaluation of the COPD phenotypes, adequately describing the disease’s physiology and clinical practice.

Commercial prostheses and orthoses are expensive and have a slow fabrication process that causes patient discomfort. This paper describes the development of an automated 3D scanning system that can reduce the time and production cost of 3D printed forearm prostheses and orthoses. The system is composed of a rotational axis and 3D scanner support, enabling the precise scanning of body parts with a shorter acquisition time and less image processing compared to existing methods. Measurements were performed to analyze the accuracy of the device. The results showed that the system obtains accurate molds of the forearm, with Technical Error of Measurement between 0.12 and 0.25%, threefold smaller measurement error than the maximum accepted value. The proposed method offers a higher number of personalization possibilities at a lower production cost, due to the use of 3D printing techniques, thereby promoting greater social inclusion.

The assessment of rest tremor can help following up the progress of Parkinson’s disease (PD). Several studies have found that low amplitude tremor may not be detected accurately. This research aims to fill this need in the area. Rest tremor was measured by an accelerometer positioned on the hand of 17 people with PD during the OFF-medication period (i.e., without drug effect). Each participant performed the hand rest task as defined in the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). The estimated MDS-UPDRS scores for hand tremor assessment was between 0 and 2 for all individuals, confirming the presence of low amplitude tremor. The tremulous activity was decomposed by Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs). The power spectral density estimated by Adaptive Sine Multitaper was employed for the identification of a physical meaning for specific IMFs. It was found that the second IMF (IMF2) represents the low amplitude rest tremor oscillating between 3 and 8 Hz. The Root Mean Square (RMS) and the Approximate Entropy (ApEn) were calculated for IMF2. The Spearman’s rank correlation coefficient was used to estimate the correlation between RMS and ApEn. The results showed that these features can be used for the quantification of low amplitude rest tremor, and that they have a strong negative correlation (ρ = −0.81), as usually observed in moderate to intense tremulous activity. These findings may be employed to detect and monitor the progress of tremor, and thus for the adjustment of drug and surgical based treatments.

For posture control, in healthy people there is an integration between lower limbs. The dominant lower limb for stabilized tasks may have an advantage in adapting automatic postural responses (APR), compared to the non-dominant lower limb. In this investigation, we aim to identify the adaptation process in the magnitude of activation of the medial (MG) and lateral (LG) gastrocnemius muscles in the dominant and non-dominant lower limbs for stabilizing tasks in repeated postural perturbation. Postural responses to repeated perturbations were assessed in the dominant and non-dominant lower limb (defined by the Waterloo Footedness Inventory adapted questionnaire) of 23 healthy young people. Postural perturbations were induced by unexpectedly releasing a load that corresponded to 8% of the participant’s body weight. The results of the study show (a) adaptation in the LG muscle, with a reduction in the magnitude of muscle activation between attempts on both legs, and (b) less activation of the MG muscle in the dominant leg when compared to the non-dominant leg. In conclusion, our results indicate that the magnitude of activation of MG and LG, between the lower limbs is asymmetric in response to unanticipated upright postural perturbations. However, the adaptation of the activation magnitude is similar between the lower limbs.

The Ludic Table is a tool for rehabilitation and development of the amplitude of movements of the upper limbs. Through it, shoulder and elbow movements are proposed because of the user’s touch on their segments. One or more tables can be combined in order to allow spatial movements; however, such association may incur in altering the rehabilitation effects. In order to understand whether different dispositions of the Ludic Tables can influence the movements of the upper limbs, three different organizations were analyzed using mathematical methods, extracting, from a set of 50 simulated anthropometric data, the amplitude of flexion and elbow extension, flexion, extension, adduction and abduction of the shoulder in each segment of the tables. Such analysis allowed to observe that the organization of the Ludic Tables has a direct effect on the groups of movements and on the methodology to be worked on by the physiotherapist. It was concluded that layout with axis of Ludic Tables aligned to the subject’s shoulder allow lateralizing the movements and privilege the work of shoulder abduction and elbow extension. Centralized formations, however, allow for a more equal distribution of movements and allow the development of the amplitude and opening of movements.

Searchers for treatments of skeletal muscle atrophy remains a challenge nowadays. Photobiomodulation therapy (PBMT) has been highlighted for clinical treatment of muscle disorders, however the molecular and cellular pathways have not yet been clarified. Thus, the aim of this study was to evaluate the effects of PBMT on molecular marker involved in muscle atrophy using an experimental model of osteoarthritis in rats. Thirty male Wistar rats were randomly divided into 3 groups: control group (CG); osteoarthritis animals control (OA); osteoarthritis animals submitted to PBMT (PBMT). PBMT (808 nm) was performed on 2 points of the knee joint. Treatment (3 days a week, for 8 weeks) started 4 weeks after the surgery. Morphometric characteristics and the immunoexpression of an atrophy marker were evaluated. The results showed that all OA groups presented a significantly increase in the muscle cross-section area (CSA) and a decrease in muscle fiber density compared to CG. Moreover, PBM presented a reduced expression of atrogin-1 immunoexpression in PBMT group. This study showed that PBMT has a positive effects on muscle wasting/atrophy, for attenuating the expression of muscle atrophy marker in an experimental model of knee osteoarthritis.

Platelet Rich Plasma (PRP) is a concentrate of platelets in a small volume of plasma. This platelet concentrate is the result of a centrifugation process for, sediment cellular constituents based on different specific gravities. The updated recommendations in the preparation of the platelet concentrate are to consider gravitational force (g) and time. Thus, the study aimed to verify the feasibility of reproducing two protocols varying forces/speed and time in the PRP recovery rate after centrifugation. The reproducibility of protocols in two different centrifuges was verified, one with a fixed rotor angle and the other with a variable angle, both with 14 cm radius. Thus, blood centrifugation was performed by the following protocols: 300 g/640 g for the first and second centrifugation, respectively, for 5 min for each centrifugation and 400 g/800 g for the first and second centrifugation, respectively, for 10 min each centrifugation. The results showed that the protocol that used centrifugation force of 400 and 800 g, both for 10 min, with a 14 cm rotor and fixed angle managed to recover a greater number of platelets. Therefore, it can be suggested that for the PRP preparation protocols to have a reliable reproducibility, it is necessary to publish detailed protocols with information on gravitational force, centrifugation time and rotor angle.

The objective of this work was to use the autocorrelation function to assess the fine motor performance of a healthy control group (CG) and people with Parkinson’s disease (PD), whose fluctuations caused by the disease compromise motor skills, performed mainly by the hands and fingers essential for daily activities such as dressing, carrying objects and taking care of personal hygiene. For this, accelerometer signals were collected while the volunteers drew a sinusoidal pattern. The correlogram was estimated and two features were calculated from it: (i) the normalized area under the curve ( $$ \varvec{AuC} $$ AuC ); (ii) the difference between matching peaks and valleys from the reference and estimated correlograms ( $$ \varvec{v}_{{\varvec{mm}}} $$ v mm ). These features allowed for the discrimination between drawing patterns of CG ( $$ \varvec{v}_{{\varvec{mm}}} $$ v mm = 0.154 ± 0.063, $$ \varvec{AuC} $$ AuC  = 0.204 ± 0.040) and PD ( $$ \varvec{v}_{{\varvec{mm}}} $$ v mm  = 0.239 ± 0.085, $$ \varvec{AuC} $$ AuC  = 0.179 ± 0.033) groups. Following the verification of normality (Shapiro-Wilk, p > 0.05), the t-test was applied to confirm the significant differences between groups (p < 0.05). The Cohen’s d effect size (p < 0.05) was medium (0.730) for $$ \varvec{AuC} $$ AuC and large (1.252) for $$ \varvec{v}_{{\varvec{mm}}} $$ v mm . This further confirms the differences between the features extracted from the groups. Therefore, the features $$ \varvec{AuC} $$ AuC and $$ \varvec{v}_{{\varvec{mm}}} $$ v mm estimated from the autocorrelation function are effective for the assessment of the motor performance of healthy individuals and people with PD.

Stretching programs are frequently used in order to reduce or avoid the risk of injury, in addition to promoting a gain in flexibility. Dynamic elastography technique (Supersonic ShearWave Imaging (SSI)) was used to analyze the changes in the shear modulus (µ) of the triceps surae tissue, in vivo, after an acute stretching maneuver. Some studies have analyzed the µ of the medial gastrocnemius (MG) and lateral gastrocnemius (LG) after an acute stretching, but data from the Achilles tendon (AT) seems to be absent. Therefore, the aim of the study is to analyze the µ of the MG, LG and the AT immediately after an acute stretch of the plantar flexors. Eight healthy young performed two stretching exercises for the triceps surae, e 3 sets of one minute were performed for each exercise. Range of motion (ROM) was measured pre and post stretching, as well as the elastographic images, for GM, GL and AT. After acute stretching, there was a significant increase in ROM (p-value = 0.033; mean pre: 34.75°; mean post: 38.50°), however, no significant difference in µ was observed for the muscles and tendon structures (GM mean pre: 5.81 ± 2.85 kPa, mean post: 7.25 ± 2.37 kPa, p = 0.200. LG mean pre: 4.89 ± 1.74 kPa, mean post: 6.49 ± 3.18 kPa, p = 0.255. AT mean pre: 128.12 ± 26.66 kPa, mean post = 108.06 ± 41.79 kPa, p = 0.168). We concluded that the stretching protocol applied in this study resulted in a significant increase in the range of motion, however, it seems not to be due to changes in the mechanical properties of the triceps surae muscle and tendon structures.

The aim of this study was to analyze the variability of coordination during gait of sedentary young people and practitioners of physical activities, at different speeds (Preferred walk speed (PWS), 120% of PWS and 80% of PWS) using the Vector Coding technique (VC). Thirty young people participated in this study, of which 15 are sedentary and 15 practiced exercise regularly at least three times a week. They performed a protocol of walking 1 min at each speed for data collection on a treadmill in a randomized order. For the Pelvis-Thigh segment, the angles were computed during four phases of the gait (first double support, single support, second double support, and swing) in the sagittal plane. The data were analyzed with a customized MatLab code. Significant differences were observed in 120% and 80% of the PWS for both groups, with greater variability in 80% of the PWS, suggesting that walking at slower speeds is a greater challenge for the neuromuscular system, when compared to higher speeds.

The aim of the present study was to quantify the variability coordination of Thigh-Leg segments, during gait, of young sedentary and active at different speeds (preferred walk- ing speed (PWS), 120% of PWS and 80% of PWS) using the previously reported modified Vector Coding technique, to record the segmental angles. Thirty young people participated in this study, of which 15 practiced physical activities at least an hour a day and three times a week, and 15 were sedentary. For data collection they executed a protocol of one-minute walking on a treadmill at each speed, in a randomized order. For the Thigh-Leg segments, the angles were computed during four phases of the gait (first double support, single support, second double support, and swing), in the sagittal plane (flexion/extension angles). The data were analyzed using a customized Matlab code. There were statistical differences for the Thigh-Leg segment pair, with great differences observed in 120 and 80% of PWS for both groups.

The aim of this study was to analyze the differences in ground reaction strength and knee mechanics joint in four jumps usually trained in ballet: Changement, Echappé Sauté 1 (fifth position for second position), Echappé Sauté 2 (second position for fifth position) and Sauté. Fifteen professional dancers participated in this study, exceeding a weekly 15 h of classes. The participants performed three trials of each jump in a randomized order on a force platform. The Sauté jump produced the greatest peak knee moment in both propulsion (< 0.001) and landing phases(< 0.001), but the lowest rate of force development in propulsion phase (0.023). These results indicate that Sauté is performed with a deeper plié in both propulsion and landing phases, with smaller ground reaction force peak and knee peak force. This pattern of jumping may be less harmful and should be adopted in the other jumps by classical dancers who perform such exercises daily several times.

Due to the high rate of accidents causing motor and neural injury, the number of victims with partial or total gait loss has been increasing. One of the main traumas is the spinal cord injury, which can cause paraplegia. Researchers face challenges to assist in the development of rehabilitation techniques, provide better living conditions for these individuals, and help in the reintegration into society. Exoskeleton are promising technological innovations and could be used here. Thus, the objective of this work was to perform a biomechanical and dynamic analysis of human gait, represented by a simple spring mass system, initially analyzing the jump. We used Matlab® to perform algebraic calculations, implement the algorithm, and data analysis. The results successfully showed the displacement behavior, speed, and power of the system to perform the jump, as well as the possibility of defining the best parameters for modeling and verification of physical and physiological limitations.

Functional electrical stimulation (FES) has been used to rehabilitate people with spinal cord injury (SCI) because it allows the control of functional movements. This work presents a knee extension control strategy that uses closed-loop FES to produce controlled functional movements in people with SCI, operating on the agonist and antagonist muscle groups of the leg. The system involved a Raspberry Pi PI controller and an Atmega328 signal generator. The frequency response method has helped to find stable values to two adjustable parameters of the controller. A low-pass filter represented the volunteer’s leg. Stimulation on the quadriceps muscle group (agonist) and quadriceps combined with hamstrings muscle group (antagonist) were tested, and the latter allowed a more effective muscle control. The simplicity of the plant and the controller resulted in some undesirable behaviors such as oscillations, which could be circumvented by the variety of parameters made available by the frequency response method.

Spinal cord injuries (SCI) can lead to body movement control loss interfering on the ambulant capability in the majority of these cases. Functional electrical stimulation (FES) was developed to soothe the consequences or aid in rehabilitation, evolving the electrical process of stimulating an affected muscle by the SCI, inducing desired movement for different ends. This project is part of a bigger goal, to successfully control lower limbs from paraplegic and hemiplegic patients during rehabilitation sessions with the use of FES-cycling, and the part presented in this paper is the validation of an electrical stimulator platform’s capability to receive closed loop control strategies applications and systems, created based on the STM boards. The validations were based on a PI controller using a range of real mathematical models, from a simple butterworth to a healthy person leg. The results obtained from the collected, treated and compared data from different stages were enough to confirm that the stimulator is capable of receiving a closed loop control system basing most affirmations on the root medium square error methodology between the gathered and reference data vectors. Results showed that all of them were below 5%, indicating a high compatibility with the base data for each of the validations.

The vertical jump is an important part of some specific skills of different sports and, therefore, numerous studies have been carried out in order to explain and assist the movement performance. The present study aims to verify the influence of the use of the upper limbs during the vertical jump movement in the variables of the Ground Reaction Force (GRF). For this, 18 female athletes from the development basketball categories performed vertical jumps with and without the use of upper limbs on a Force Platform (AMTI). The average of 3 valid jumps from each athlete was used for statistical analysis using the paired t test. The tests were performed using the SPSS v.20 software and the significance level adopted was 0.05. Significant differences were found for GRF in the eccentric phase, in the duration of the aerial phase and in the maximum height reached during the jump. The % of GRF in the eccentric phase in the jump without using the upper limbs (0.58 ± 0.21% Body Weight) was significantly higher than in the jump with the use of upper limbs (0.48 ± 0.22% Body Weight), however in the duration of the aerial phase the jump performed with the aid of the upper limbs (0.48 ± 0.04 s) was greater than in the jump performed without the aid of upper limbs (0.43 ± 0.05 s), in accordance with the maximum height which was also greater in the jump performed with the use of upper limbs (0.28 ± 0.05 m) than in the performed jump without the use of upper limbs (0.23 ± 0.05 m). As the conclusions of this study, the practical suggestion is to help them jumping with greater speed avoiding dissipation of the energy accumulated in the eccentric phase.

Postural changes that result from musculoskeletal disorders and habits related to activities of daily living, have directly influenced the individual's functionality. The maintenance of an inadequate individual's posture can result in several types of comorbidities, such as contractures and deformities. Wearable and interactive technologies can minimize such injuries, as they have sensors for movement analysis in the most diverse conditions, furthermore help in postural's perception and avoid maintaining vicious postures. The objective was to develop a wearable and interactive system for detecting postural aspects through accelerometers and sending information in real time to the user. This research was approved by the Research Ethics Committee under CAAE: 06276819.6.0000.5208 and it is a pilot study. The wearable system consisted of a microcontroller, a Bluetooth module and accelerometers, those were strategically distributed in the prototype's clothing. After the prototype design, pilot tests were performed on a volunteer to analyze the system's responsiveness, reliability and viability to a variety of trunk's postures. In the tests performed, it was found that the prototype was effective in detecting postural changes in various forms of orientation and inclination, making it possible to detect postural compensations in comparison to its reference axis, previously configured during the calibration phase. The developed system is responsive to the individual's posture, providing visual and tactile alerts, enabling a better postural adaptation. And as it's a low-cost and easy-to-use instrument, it will be able to subsidize the user by offering feedback to minimize future problems and even in future research and applications.

Parkinson’s Disease (PD) is a chronic, progressive and degenerative disease that causes the death of the dopaminergic neurons. Clinically, PD is characterized by tremor, stiffness, slowness in movement and changes in posture, balance, and gait. The hand is one of the regions in the body most affected by bradykinesia due to the evolution of the disease. The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is the most widely used clinical scale to follow up the clinical condition of patients. The aim of this work is to review the literature on hand movements included in the MDS-UPDRS Part III (Motor Examination) and also to analyze flexion and extension movements not included in the MDS-UPDRS. The main hypothesis of the study was that flexion and extension movements, not included in the MDS-UPDRS, are important for the clinical evaluation of patients with PD. To verify this hypothesis 23 studies have been identified and analyzed. These studies considered the evaluation of PD motor signs of based on tasks such as finger tapping, hand opening and closing, hand supination and pronation, and hand flexion and extension. The results show that hand flexion and extension are important activities for the assessment of motor signs in people with PD, even though they are not included in the MDS-UPDRS.

The access to new technologies is growing worldwide. Nowadays, children under two years old already have some type of digital device, which can decrease hinder your time in gross motor experience, then limiting development of basic motor skills and gross motor coordination during childhood. Since the sedentary lifestyle in children has been increasing more and more, it is important to introduce technological resources associated with traditional physical activity programs. The use of active games or the so-called exergames together with traditional physical exercises can contribute to the development of motor skills and coordination in children. Motor development is the continuous change in motor behavior throughout the life cycle caused by the interaction between the demands of the motor task, the biology of the individual and the conditions of the environment. The environment can be then seen as a great ally of motor development and can help determine the future conditions of a child. We revised the studies about the exergames effects on motor development in childhood. From the analysis of several scientific studies, it was possible to conclude that virtual games combined with physical education classes contribute to the improvement of motor skills and gross motor coordination in children.

This study aimed to compare the modulation of time and frequency-domain EMG parameters between trained gymnasts and healthy untrained controls during a protocol designed to induce muscle fatigue on the ankle plantarflexor muscles. We hypothesized that neuromuscular adaptation due to training would lead to different behavior of EMG quantifiers along the fatiguing process. Twenty eight female volunteers (aged 11 to 26 years) were recruited and two groups were formed: acrobatic gymnastics athletes (GYN, n = 14) and non-gymnasts (control (CTRL), n = 14). Fatigue of the ankle plantarflexors (dominant leg) was induced by a sustained posture (standing on the toes) until exhaustion. Surface EMG signals were acquired from the tibialis anterior (TA), soleus (SO), lateral gastrocnemius (GL), medial gastrocnemius (GM), vastus lateralis (VL), biceps femoris (BF), spinal erector (EE) and rectus abdominis (RA) muscles. EMG amplitude (aEMG) and median frequency (Fmed) were computed in 3 different periods of the fatigue protocol: (1) during the initial 10 s, (2) during the central 10 s, and (3) during the last 10 s (final period). The results showed significant increases in aEMG values and significant decreases in Fmed values throughout the fatigue protocol, for almost all muscles investigated, indicating a fatigue effect that was not restricted to the target muscles (plantarflexors). Differences in muscle activation patterns (in both time and frequency-domain parameters) indicated that acrobatic gymnastics athletes, as compared to healthy untrained participants, used different neuromuscular control strategies during the sustained fatiguing isometric contraction.

This study aims to analyze the amputation rates in Southeast Brazil, the most populated region in the 6th country regarding the largest population in the world. In consequence, the national literature does not have solid results of total of amputation rates. Therefore, this study shows the incidence rates of amputations (per 100,000 inhabitants) in Southeast of Brazil. The state of Rio de Janeiro, presented the highest incidence of lower limb amputations and Espírito Santo, the highest incidence of upper limb amputations. The rehabilitation generated by the national technology needs to be more developed in Brazil. Focusing on reinsertion of amputees in society and generate a better quality of life to brazilian inhabitants.

3D printing is an emerging technology for the manufacturing of prostheses with the potential for low resource configurations. However, studies using flexible materials to improve prosthesis properties are still scarce, such as adaptability, flexibility, fewer joints, among others. Thus, this paper is aimed to manufacture and evaluate the applicability of a flexible finger prosthesis using 3D printing. For this purpose, analyzes of finger positioning, scanning, and modeling were performed. The prosthesis was manufactured using TPU and fabricated on a 3D printing machine. Finite element analysis was also applied in order to assess the functional aspects of the prosthesis produced. After that, it was possible to manufacture the prosthesis in one piece, reducing manufacturing time and problems associated with subsequent assembly.

One of the major difficulties faced by upper limb prosthesis users is the absence of tactile sensory feedback, which is fundamental to handling objects. Tactile feedback is required to estimate texture and shape of objects, enabling the subject to adjust the forces required to manipulate things and avoid slip. In the absence of tactile sensory feedback, the users become dependent of other kinds of feedback, such as visual or auditory, which are not effective every time. Aiming to overcome the limitations encountered by upper limb prosthesis users, we developed a protocol to characterize sensation caused by a modulated frequency transcutaneous electrostimulation. We realized that the frequency modulation can change the haptic intensity and that the amplitude of the stimulation directly influences the perception of the frequency change and the intensity of the perceived sensation. While the threshold of perception of discrete or continuous stimuli varied for each volunteer, the volunteer V1 did not have the perception of continuous sensation in the frequencies used, and V4 had this perception only with the amplitude of 1 mA. While for volunteers V2 and V4, this threshold was 50 and 100 Hz for the three experimental blocks, respectively. The volunteer V5 and V6 had different thresholds according to the stimulation current.

The static stretching with both hip flexion and knee extension is often used to stretch the hamstrings, composed of the biceps femoris (BF), semimembranosus (SM) and semitendinosus (ST). However, it is unclear whether there are the differences in stiffness among each component of the hamstrings immediately after a stretching session, either for physical conditioning or rehabilitation. The purpose of this study was to investigate the difference in the hamstring shear modulus after an intervention of static stretches. The shear modulus of the ST, SM and BF muscles were measured using ultrasound shear wave elastography before and immediately after the stretching protocol. The results suggest that static stretching was able to increase range of motion (ROM), but it was not due to changes in the stiffness of the hamstring muscles. After stretching, the BF showed a difference in relation to the SM and ST. In addiction, ICC for the hamstrings in a relaxed position showed good reliability. These results suggest that stretching exercises commonly used in flexibility training are capable of increasing the ROM as an acute process independent of changes in muscle stiffness.

This article was elaborated based on data acquired from February to June 2019, with experimental observational character. The interest of this study was to implement the application of a tool, a Serious Game, as a strategy to complement the traditional physiotherapeutic approach and assist the rehabilitation process of children using Orthosis Dennis Brown, aged 18–36 months. This process was based on three fundamental steps (1) electronic suitability of a commercialable toy in a Serious Game with the necessary characteristics for a child with congenital crooked foot; (2) creating an electronic circuit to control the game; (3) inclusion of a wooden platform for positioning the feet. During the planning phase of the electronic system of the Serious Game, aimed to create an interface to be used together with the children, in order to allow the interaction child with the serious game only in the crouched position; monitoring and delimitation, by sensors, of the positioning of the feet on the wooden platform; freedom of movement of arms and hands during fun. The keyboard mat has been changed and appropriate electronically. As future perspectives it’s intended to promote tests and verify the applicability of the Serious Game to be used in the rehabilitation of children with Congenital Clubfoot who use Orthesis Dennis Brown. Recognizing the needs of these potential users is essential to plan and implement new technologies according to their specific demands. Publications in this line of technological research are an expanding field, as well as the need for future research.

This article presents a Serious Game, a playful tool, that can aid physiotherapeutic treatment in children with Congenital Clubfoot, also known as Congenital Talipes Equinovarus (CTEV), aged 18-36 months, who use Dennis Brown Orthotics (DBO). The main objective is to encourage them to squat, a natural position for this age group. The sample consisted of 47 children, 11 with congenital crooked feet. The test and applicability of the Serious Game occurred through the analysis of the degrees of interest and interaction of each volunteer child with the Serious Game; as well as the ability to measure the time spent during your entertainment. The results found were: (1) 81% of children with clubfoot corresponded and/or exceeded the time of 5 min in the squat position; (2) 25% of children with clubfoot, 40% in 2-year-old children without congenital anomaly and 6% in 3-year-old children were able to interact with the Serious Game in the crouching position; (3) 85% of children with clubfoot, 48% of 2-year-old children without anomaly, 98% of 3-year-old children without anomaly interacted with the Serious Game; (4) The Serious Game was accepted by 90% of the children with clubfoot, 75% of 2-year-old children without congenital anomaly, 80% of 3-year-old children without congenital anomaly. From the proportions obtained it’s suggested that the children, mostly independent of age and congenital condition, accepted and interacted with the Serious Game, which makes it possible to provide evidence about the Serious Games to assist in the rehabilitation of children who use the Dennis Brown Orthotics, and to direct new research fields both at the level of Biomedical Engineering and Physiotherapy.

The choice of the brain area to be stimulated by non-invasive brain stimulations (NIBS) often poses a challenge to physiotherapists. To address this issue, a mockup design of a Decision Support System (DSS) application called SMDQ App was created following the Design Thinking (DT) methodology. As a part of this method, SMDQ App 1.0 was tested, and based on this testing a second version was elaborated (SMDQ App 2.0). Again, tests were made to the second prototype version, and feedback was collected. The application of two rounds of tests is common when using DT and enables a better understanding of users’ needs, thus improving the acceptance of the tool. SMDQ App 1.0 had Ok usability according to the System Usability Scale. With the improvements, SMDQ App 2.0 was classified with Good usability.

This study aims to verify the most recurrent patterns and mechanisms of shoulder injury in users of manual wheelchairs with spinal cord injuries. A bibliographic survey was carried out in scientific articles written in English and Portuguese at the following databases: SCIELO, LILACS, PubMed, BVS and MEDLINE. It was found that although pain is a physiological alert mechanism for the abled body, shoulder pain in spinal cord injured people is very common at different times after the spinal cord injury and the mechanisms of shoulder injury in wheelchair users are multifactorial. Thus, it appears that shoulder pain is present in both sedentary and non-sedentary wheelchairs users. It is also common for users to abandon manual for motorized wheelchairs. It can be concluded that the shoulder injury is frequent in wheelchair users, thus hindering their occupations and quality of life. Therefore, it is important to have a rehabilitation program even after the initial rehabilitation, to maintain physical and functional gains, as well as the development of assistive technologies to favor their quality of life and the occupational performance of wheelchair users.

Congenital clubfoot is an orthopedic manifestation characterized by poor alignment of the foot as deformities in equine and varus of the hindfoot, cavus and adduction in the middle and forefoot. The Dennis Brown Orthosis is part of the final phase of the treatment of pathology in children. This research presents the development of a prototype of Dennis Brown Orthosis by additive manufacture, with experimental observational character to enhance production performance and viability. Methodology: The research was divided into four phases: 1. 3D modeling of the Dennis Brown orthosis based on anthropometric measurements of a positive infant foot cast of plaster and digital file; 2. Analysis of the mechanical structure of the orthosis by computational simulation with the finite element method; 3. Production of orthosis by additive manufacture with 3D desktop printer Anet A8 and polylactic acid material (PLA); 4. Study of the technical and financial feasibility of the use of the manufacturing methodology adopted. Results: A prototype of Dennis Brown children's orthosis customized was manufactured with digital equipment and the cost was nearly to the commercial model of orthosis made in orthopedic in a handmade way. In addition to lowering costs, the model produced by 3D printing has advantages of minimizing production time and reducing material waste. In addition, because it is manufactured through a digital file, the procedure can be done from 3D scanning without molding the child's foot with plaster, and the production procedure can be repeated as many times as necessary. Conclusion: The research presented feasibility from the technical and financial point of view of the application of additive manufacturing in the process of making a prototype of Dennis Brown Orthosis. In the next phase of the research, clinical evaluations will be carried out with volunteers.

The human body is an articulated system that, among other movements, presents a set of essential information in gait on the first assessment of body condition. Due to its complexity, an in-depth analysis of this movement requires interpretations that involve all biomechanics. In this context, this work's general objective was to analyze and interpret kinematic data, responsible for describing the movement quantitatively by values of displacement, velocity, and acceleration of the body. For this, two types of data collection were performed, one through the filming of the individual in their gait movement, in which strategic posterior markings were made on the foot and knee in each frame of the video, using the MATLAB software, and the other through the MPU-92.65 accelerometer sensor associated with an Arduino microcontroller board and manipulated by MATLAB software. The objective of carrying out these two acquisition methods is to compare these analyzes and verify the results obtained. This study revealed that the two methods showed similar results when analyzing the knee speed curve. However, due to some movement artifacts, the same result cannot be obtained for the foot speed curve.

High-density electromyography (HD-EMG) signals have been widely used today due to their ability to extract spatial information from muscle activity. Several studies pursuit a pattern of activation of the fingers with the muscle activation center using several types of different protocols. This work aims to develop a feedback protocol for finger recognition using HD-EMG. The tools for the analysis were the activation centroids of each finger in addition to the use of the non-negative matrix factorization (NNMF) algorithm to extract the associated synergies of each finger and dissociate them. The protocol elected in this research proved to be effective in the selection of index and minimum fingers. In addition, an ANOVA statistical test application on synergies showed great utility in dissociating fingers.

Forward dynamics simulations of musculoskeletal systems allow predicting joint movement from neuromuscular excitations. OpenSim models present several nonlinearities that make classic control synthesis and closed-loop movement simulation a challenging task. In previous works, we designed closed-loop controllers, based on linear assumptions, for the identification and design of an $$\mathscr {H}_{\infty }$$ H ∞ controller in series with a reciprocal inhibition architecture, to control an OpenSim wrist biomechanical model. Here, we present an optimized and simplified closed-loop controller, using only the reciprocal inhibition module. Genetic Algorithm optimization of a quadratic cost function was employed to tune the controller parameters. Setpoint control from different initial conditions was tested. The lowest cost controller resulted in rise and settling times for flexion of approximately 68 and 162 ms, respectively. For pronation, 34.3 and 168 ms. Such results, which agree in shape, rise, and settling times with those obtained experimentally on literature, suggests that an appropriate controller structure was selected and tuned. Therefore, a GA-based control design of a reciprocal inhibition architecture seems to be an appropriate approach to handle forward dynamics closed-loop simulations of musculoskeletal systems.

The present study aimed quantify the variability of segmental coordination, during the gait of young practitioners and sedentary people on different slopes (Horizontal, 8% and 10% Upward (Up) and Downward (Down) conditions) maintaining the self-selected speed (VAS), using the Vector Coding technique. Thirty young people participated in this study, of which 15 were sedentary and 15 practiced physical exercises at least one hour a day, three times a week. They per- formed a protocol of walking 1 min on a treadmill on each inclination for data collection, in randomized order. For the Pelvis-Thigh segment, the angles were computed during the four phases of the gait (first double support, single support, second double support, and swing), in the sagittal Flat. The data were analyzed using a customized Matlab code, how had a normal distribution, an ANOVA was used to classify. There were significant statistical differences for the Simple Support and Swing phases, with greater variability for the slope situation.

Foot placement is important for stability during gait, as it contributes to individual’s dynamic balance since location of the foot determines the origin and possible directions of the ground's reaction force. The objective of this study is to perform the step by step prediction of the heel marker in anteroposterior and vertical direction during the cycle of a gait step using Kalman Filter. We intend to validate a methodology that leads to construction of a more complex system of foot placement prediction to improve gait stability. The real displacement of the marker was obtained through an image processing from the 2D video capture system of a volunteer in a controlled environment. The results presented errors less than 3 cm in prediction of the heel position, showing that Kalman Filter is a potential tool for this application.

The present work seeks to provide a reliable estimation of Achilles tendon (AT) mechanical properties, especially the maximum tangent modulus (ET max) and its relationship with respect to deformation, comparing long-distance runners and pentathletes. Six pentathletes and six long-distance runners (different weekly running training volume than pentathletes (116.7 ± 13.7 vs. 58.3 ± 20.4 km, p < 0.01)). From the analysis of ET curves, it can be observed that the long-distance runners’ group presented higher ET max (380. 6 ± 92.22 vs. 36.2 ± 82.6 MPa, p < 0.05) and maximum true stress than pentathletes (24.2 ± 5.1 vs. 16.0 ± 3.5 MPa, p < 0.05). The higher AT ET max of long-distance runners suggests a higher material stiffness in the group that trains the highest weekly run volume, as well as higher AT elastic energy storage capacity. This approach can be used as a tool for evaluation and monitoring of high-performance running athletes.

Exoskeletons are promising technologies in rehabilitation medicine, since they help debilitated patients to improve their motor skills, thus increasing the quality of life of these individuals. Therefore, the purpose of this work is to demonstrate the initial processes of making an adjustable and personalized lower limb exoskeleton for children, based on the understanding of the neuromusculoskeletal system and characteristics of human gait. In addition, the study of this robotic orthosis involves investigating its applications, performance systems, structural components, advantages, and disadvantages. As part of the initial processes, a programming test was performed in open-source software named Tinkercad, to control the hardware and gait timing, followed by the simulation of the actuation system to obtain an exoskeleton as functional as possible. Simultaneously, the device's structure was modeled on Autodesk Inventor software, which will allow a stress analysis. Once these steps are finished, the final assembly and tests are carried out, which will consist of an adjustable exoskeleton with two Degrees of Freedom (DOF) in each lower limb.

Worldwide, as the average life expectancy increases, the number of people in need of physical therapy rises. As a means of turning therapy more efficient and engaging, serious games have been developed for virtual reality environments. At the same time, in order to aid the user to perform the exercising movements, robotic devices have been employed along with these rehabilitation games. In the context of telerehabilitation, communication between devices is crucial since a seamless communication among many computers is a requisite. Having this in mind, this work proposes a remote control architecture for computers connected to the same local network, which will serve as a proof-of-concept for further applications where the communication among the robot device, the virtual reality application and other auxiliary computers is needed. This paper introduces briefly a robotic device for ankle rehabilitation and the control scheme, shows the development of a virtual reality racing game and introduces a third element, the physiotherapist computer, which can change remotely the robot resistance, thus increasing the game difficulty. It is crucial to guarantee that the physiotherapist has control over the robot parameters as well as access to the patients’ data in order to adapt their experience according to their performance.

Intramedullary nailing has been used to support long fractured bones, as femur, during the healing process. The load shared between bone/callus and intramedullary nailing is a function of the callus stiffness, that in turn varies during the healing process. Thus, the available mechanical load at callus region during the healing process can define the healing effectiveness. Therefore, the shared load between intramedullary nailing and bone/callus must be accessed. To reach this objective, an analytical model, based in mechanics of solids, is presented to describe the evolution of the load share between bone/callus and intramedullary nailing, at callus region, during the healing process.

In this work, an analytical model of porcine knee ligaments, statically loaded, is presented. Although introductory, this elastic analytical model provided an estimative of the main mechanical variables results, as longitudinal forces and displacements, and its respective longitudinal stresses and strains, in each of four knee ligaments: lateral collateral ligament (LCL), anterior cruciate ligament (ACL), posterior cruciate ligament (PCL) and medial collateral ligament (MCL). An interesting conclusion of the application of this analytical model was that the cruciate ligaments were submitted to greater forces than the collateral ones.

This study aimed to compare the anterior–posterior ground reaction forces (GRF) between children and older women during gait. Twenty-five girls (6.39 ± 1.88 years) and thirty-three elderly women (70.48 ± 6.66 years) took part in this study. Participants were asked to walk along a 6.0 m walkway with 8 force platforms. The GRF was sampled at 1000 Hz and the data recorded were from both lower limbs. The analysis focused on anterior–posterior GRF and the variables related to the braking and propulsion phase of walking. Braking peak, propulsive peak, time for braking peak, and time for propulsive peak are significantly greater for children than for elderly women (p < 0.001). The differences observed in the gait anterior–posterior GRF between children and elderly women are evidence of age-related effects on gait variables, and that this evidence can be used for exercise interventions aiming to improve gait in children and older women.

Clinical gait analysis is essential to measure and interpret biomechanical parameters related to locomotion. It may assist health professionals while choosing the most appropriate interventions. This study aims to compare biomechanical parameters of the gait of children of different ages and to contrast these findings with the literature. Gait data from children aged 3–9 years old were collected using force platforms. Ground reaction forces were analyzed using an Octave routine. The implemented algorithm allowed the extraction of specific values of force and time. These values are following the literature and shown a well-established biomechanical pattern. However, no differences were found in the biomechanical parameters between the studied age groups. These findings allowed for interesting reflections that were made analyzing and interpreting the results and extrapolating those evidence for the force–time profile of the GRF and its development along with childhood.

People with complete spinal cord injury (SCI) present a rapid process of muscle fatigue under neuromuscular electrical stimulation (NMES) due to neuromuscular impairment. Different NMES patterns interfere with the fatigue process and joint amplitude. The aim of this study was to evaluate muscle reactions using joint knee joint fatigue protocol with four NMES patterns in people with complete SCI. Ten subjects with complete SCI were submitted to 4 stimulatory profiles, with varying pulse duration and the modulating frequency (burst): P1 (100 μs–50 Hz); P2 (100 μs–70 Hz); P3 (200 μs–50 Hz); P4 (200 μs–70 Hz). Subjects were classified according to theirselves angular responses as upper median (UPmed) and lower median (LOWmed). UPmed had lower angular variation and attenuation in the fatigue process than LOWmed in P1 (session I, trial 1 p = 0.06, trial 2 p = 0.009, trial 3 p = 0.029, session II, trial 1 p = 0.015), P2 (session I, trial 3 p = 0.024, trial 4 p = 0.034), P3 (session I, trial 3 p = 0.035), P4 without intergroup difference. The angular variation can be applied as a useful tool for muscular condition classification of complete SCI people. The best performance of UPmed has occurred in P1 and the worst in P4. The LOWmed performance did not stand out in any protocol.

The aim of this study is to describe kinematics, dynamics, and muscle synergy differences between horizontal and vertical jumps, considering the propulsion and landing phases. We analyzed thirteen healthy women that performed jumps in the horizontal and vertical directions. The biomechanical variables were calculated solving inverse kinematics and inverse dynamics problems. The algorithm of Non-Negative Matrix Factorization was used to estimate muscle synergies based on EMG envelopes. We observed that knee joint had important differences between the both phases, mainly in the VP and VL, because present greater joint moments and that pattern is associated with injuries risks. Kinematics and dynamics differences can show us deficits in the execution of movement patterns and what is the best test for evaluating clinically relevant variables. Furthermore, it was possible to associate muscle motor control patterns to kinematics and dynamics variables to determine how the muscles work during each phase of both tasks.

The present work addresses the development of a respiratory simulator for neonatal applications that is able to interact with mechanical ventilators in its 3 main ventilation modes: spontaneous, controlled and assisted. However, for this project scope, only controlled pressure feature is focused within these 3 modes. In order to abide such requirements 2 mathematical models were developed. The first is relative to the neonate’s respiratory system and the last one is associated with the simulation plant, meaning the equipment which is going to reproduce the respiratory patterns from the model. From the biological perspective, a parallel 2 compartment model which includes a central resistance and a compliance that emulates the rib cage was developed. The utilization of a multicompartmental model allows the emulation of heterogeneous respiration. In addition, it is possible to extrapolate and include as many compartments as needed for the application. On the other hand, a syringe pump based device was chosen as the simulation plant due to the compatibility of this mechanism’s features with the requirements needed to emulate, with high precision, neonatal respiration, such as small volumes, small airflow and pressure. Its mathematical model was derived from mass conservation law and it relates directly to the inlet/outlet airflow with angular velocity of the lead screw mechanism which drives the piston movements. The simulations were conducted on Matlab/Simulink environment, where the respiratory model input signal corresponds to the ventilation mode chosen by the user. In general, the results showed that the device was able to track airflow and volume reference signal within a 3.5% error margin for all ventilation modes.

A brief review of the literature on the use and clinical significance of recurrence quantification analyzes for kinematic and kinematic data is presented. The common recurrence quantifiers used in biomechanics, as well as their theoretical significance, are presented. Next, an overview of the studies in which recurrence quantifiers are used is presented, showing their association with other nonlinear quantifiers. The influence of parameters, such as sampling frequency, definition of the minimum size of the diagonal lines and length of the time series, is investigated. Although there is different approaches for parametrizing and applying recurrence quantification analysis to biomechanical data, recurrence quantifiers can extract information from data with low time resolution while maintaining the reliability of results. More importantly, the use of recurrence quantifiers in clinical trials allows for discrimination between experimental and control groups.

Cognitive and motor development are important issues in patients with special needs, such as Down Syndrome (DS) or Autism Spectrum Disorder (ASD). The difficulty that individuals with DS and ASD present in the acquisition of motor and cognitive skills has motivated scientists to study and develop means of intervention. The application of technology has improved the traditional way of dealing with therapies, especially with the development of virtual environments. In this sense, serious games can create an immersive environment from recreational resources to assist in rehabilitation and physical and motor training. Motion analysis can be made in a virtual environment through the estimation of joint angles and trajectories. This can help health professionals in a quantitative way to analyze motor and cognitive rehabilitation. This paper aims to show a proposal of virtual environment to be applied in the rehabilitation of motor and cognitive functions of people with special needs. The system consists of a depth camera (RGB-D) and a projection interface for serious games. A protocol of data acquisition based on the tasks performed according to the game is proposed. Preliminary tests with a healthy subject were made. The results are the establishment of the virtual environment: a game was developed that involves motor tasks but also includes cognitive development. Joint angle and trajectory estimation are shown. A comparison which involves the movement and the time of response of the subject performing the task between the trials in the protocol is also made. The proposed technique for joint angle and trajectory estimation demonstrated to be a feasible and straightforward option to obtain kinematics analysis from playful tasks performed in a markerless system.

Transtibial prostheses have the function of replacing the amputated limb and its constructive characteristics are extremely important for the mobility of the user. Active prostheses are characterized by adding and dissipating energy during walking in a controlled manner. Over the years many researches have been dedicated efforts to develop more suitable prosthetic for the user, the main challenge is to develop a device with power and performance speed suitable for the function in a light and compact structure. This work aims to develop a kinematic model of a bionic foot for transtibial amputees and to tune a controller for the ankle angle in order to enable the proper selection of the system components.

Stroke is the leading cause of impairment and residual mobility problems in the world, but most of the victims are able to recovery partially after rehabilitation treatments. This paper concerns the development of a 5 degrees-of-freedom parallel robotic structure designed to assist the human gait rehabilitation process, working as an active body weight support for treadmill or overground exercises sessions. The structure applies an assist-as-needed design to stimulate balance control, motor coordination and posture correction during the gait. The system is also integrated with an electronic game developed to enhance the experience of the patients while performing the training sessions. The structure mathematical model and the first control tests are done, while the actual running research is performing the first experimental tests and clinical trials.

There are different types of dance turns, such as pirouettes, fouettés, and single leg turns. Besides, these turns can be performed with different body positions and combinations. Therefore, this study aimed to compare displacement of the center of mass (CoM) of the body, head and thigh, and knee flexion of the gesture leg, between the positions of the coupé and passé legs during the Single Leg Turn of the Brazilian Zouk, in which the follower dancer performs a rotation along its longitudinal axis conducted by the leader dancer. The Single Leg Turn is an important movement in competitions and the location of the CoM is essential for maintaining the dynamic balance of the turn. The movement of a follower dancer was recorded by 18 cameras (Prime 13, 240 Hz), OptiTrack system, Motive software (version 1.10.0 Beta 1), for acquiring and digitizing trajectories of reflective markers. Datas were processed using Visual 3D software (version 5.02.11) and average of the attempts was analyzed. The evidence found suggests the occurrence of adaptive changes to maintain the dynamic balance in the Single Leg Turn in relation to the displacement of the CoM of the entire body in the mediolateral axis and in the flexion of the right knee in coupé and passé positions, which can be linked to the pattern of the dancer herself or to the conduction by the partner.

In this study, we describe a system to automatically analyze rowing kinematic parameters using video capturing and processing and using a single RGB camera. Useful rowing 2D joint angles in the sagittal plane are estimated using the OpenPose API combined with an offline filter to overcome frame loss and oscillations. Rowing key moments are identified using a time series comparison between the joint angles curves from the movement performed and a manually labeled reference joint angles curves, representing a desired rowing stroke. The comparison is realized using the Dynamic Time Warping method. All the obtained data is displayed in a user-friendly interface to monitor the movement and provide offline feedback. The proposed approach enables automatic analysis of video-recorded training sessions.

The use of smartphones by Brazilians in vehicles subject to vibration is increasing. Consequently, the analysis of the transmissibility of seat-to-hand vibration becomes necessary. Tests on a vibrating platform were developed in order to assess the influence of frequency, amplitude, gender and type of smartphone on this transmissibility. Six different stimuli (three frequencies and two amplitudes) were applied to volunteers who used two types of smartphones. The results showed that transmissibility increased with decreasing frequency and amplitude. In addition, the change in frequency or amplitude did not cause proportional behavior in transmissibility. In relation to gender, men accentuated the vibration compared to women, indicating less capacity to reduce vibration. As for smartphones, they had no influence on transmissibility.

Through the study and analysis of motor primitives, it is possible not only to perform motor control to aid impaired people, but also to develop techniques for neuromuscular rehabilitation. Human motor control is executed through a basic set of signals that govern the motor behavior. This basic set of signals is called primitive motor movements. From the knowledge of an individual’s motor primitives, it is possible to develop control strategies, which are capable of assisting individuals with some sort of mobility impairment. In order to extract these motor primitives in a precise way to carry out the development of assisting devices, factorization techniques are fundamental and many methods exist to perform this task. The present work analyzes the results yielded by four of the most used matrix factoring techniques (PCA, ICA, NNMF, SOBI) using electromyography signals. The results suggest that the PCA is the technique that best managed to reconstruct the EMG signals after their factorization, with a virtually zero relative error. The SOBI technique also yielded satisfactory results, followed by NNMF and finally ICA, which presented a reconstructed signal quite different from the original.

In order to assist physiotherapists during the process of rehabilitation of individuals, especially after anomalies in the neuromusculoskeletal system due to diseases such as stroke or injuries, different types of orthoses for lower limbs and controls for these orthoses have been developed. This work aims to develop a robotic control strategy based on kinetic motor primitives, capable of assisting the recovery of patients with compromised movements. The primitives are calculated from the torques obtained by OpenSim’s Inverse Dynamics, which are used as input into the scaled model of the subject that used the orthosis along with the positions provided by the encoders of the orthosis fixed to the knee joint of the subject, who performed the extension/flexion movement. The proposed strategy was evaluated using a Forward Dynamics algorithm, through which new knee position data were obtained.

This paper presents the mechanical design of an active hip and knee orthosis for rehabilitation applications. The exoskeleton device consists of two motorized joints providing 2 DOF per leg and can support a non-standard critical user (1.90 m in height and 100 kg in weight) in rehabilitation gait conditions (gait speed $$\approx $$ ≈ 0.3 m/s). The work’s methodology is firstly established with literature review to explore relevant orthotic projects already developed. Then, project requirements are defined, including critical user conditions, joint restrictions and rehabilitation gait torques and angular motion. The exoskeleton’s structure is modelled following critical static and dynamic conditions and solved analytically for static failure and stiffness criteria. The actuation drive components are designed based in numerical modelling and also solved for static failure and stiffness criteria. The project’s mechanical components are then designed following the results once they reached acceptable safety levels. The mechanical components can be subdivided into three main groups: lumbar support, limb structural links and actuation drives. Those groups a integrated to construct a prototype of the orthotic device. The assembled prototype presented the aimed robustness when tested for basic motion control associated with a equivalent rehabilitation gait pattern with artificial loads. The test trials showed low levels of induced deflection and the actuation drive was able to replicate the torques required, therefore, making the orthosis to meet successfully the intended mechanical prerequisites.

This paper presents a systematic literature review method and a bibliometric analysis for the topic “Lower limb exoskeletons for rehabilitation applications”. The method can also be applied to other topics. Five databases were chosen for documents search, which are: Web of Science, Scopus, IEEE Xplore, Catálogo de Teses e Dissertações (CTD) and Biblioteca Digital de Teses e Dissertações (BDTD) of CAPES. All the results presented in this paper were obtained on December 31, 2019, as they might change with time. To make the review reproducible, updatable and continuous, a review protocol was created. Results from the secondary analysis were further analyzed, presenting the best “top 10”: most prominent research areas, most highlighted research countries, sources with the highest register of documents and, most cited documents from Web of Science and Scopus respectively. However, in the bibliometric analysis, VOSviewer tool was used for the co-authorship, co-citation and bibliographic coupling analyses, while TagCrowd was used for keywords co-occurrence analysis. The work is concluded with some important considerations observed during this analysis.

Lower limb exoskeletons are wearable robots worn by human operators for various purposes. Their design, control and biomechanical aspects have been discussed in many publications in the literature. However, there is a gap in their robotic nature analysis, and few documents discussed the biomechatronic aspect of the robotic devices. In this scenario, this paper presents a brief analysis of the biomechatronic system’s components of lower limb exoskeletons for augmentation and rehabilitation applications. In this case, the biomechatronic system is considered to have five components, which include: Mechanisms, Actuators, Sensors, Control, and Human–Robot Interaction. A literature review was initially conducted to explore documents with the highest relevance to the topic for analyses. Therefore, in Mechanisms: metabolic cost, biomechanics of walking, average human walking speed, mechanics of human movements, movements at the hip, at the knee and at the ankle joints are addressed. In Actuators, different types of actuators used by different projects from the literature such as electric motors, series electric actuators (SEAs), pneumatic, hydraulic, and pneumatic muscle actuators are analyzed. In Sensors and Control, different types of sensors and control strategies adopted by different projects are also analyzed. In Human–Robot Interaction, cognitive human–robot interaction and physical human–robot interaction are discussed. Finally, the work is concluded with some important considerations for this analysis.

This article presents a numerical methodology for the kinematic analysis of planar mechanisms based on the closed loop method. Initially, the mesh is defined with the aid of complex notation and, through iterative processes, the configuration of the mechanism is defined as a function of time. For the calculation of speeds and accelerations, the 4th order numerical derivative was applied. After applying the procedure, satisfactory results were obtained for a certain step size range, showing itself as a useful tool for kinematic analysis.

The present work deals with the development of a low cost mobile partial weight suspension (PWS) device. PWS is a technique used to treat people with motor disorder. There are some PWS systems on the market that perform similar functions but are not financially viable to a large public. Other than that, those systems do not allow adaptations. Initially, research was carried out at a university clinic to collect information on the problem. Afterwards, the project started, so that it would meet the established requirements. The device is based on a structure made out of circular steel tubes fixed by pins, a ratchet system and pulleys for adjusting the height of the suspension belt. To validate the structure, a static simulation of finite elements was performed. Finally, a low-value device was projected for satisfactorily compliance of the requirements imposed by the clinic’s physiotherapy team.

In this work, the mechanical project of a machine for tests in transtibial prosthesis is proposed. The system is developed as a robotic mechanism that executes movements above the prosthesis to reproduce the human gait. However, instead of usual devices that implement a model for a single axis movement, this work employs a user similar gait to test a prosthetic device. Thus, this approach is more realistic, as it allows the test of a prosthesis for different types of gaits and different global movements, such as the climbing of a stair. To accomplish this objective, three steps are proposed. Firstly, image analysis is extracted from human gait. Then, the movements are converted to the mechanism’s joint angles. Finally, the robot performs the gait based on these angles. Although it is an initial approach, open-loop simulations demonstrate that it is useful for the study of the dynamics of an orthopedic prosthesis, as well as to perform fatigue analysis of this kind of equipment and even to verify the integrity of the prosthesis to guarantee the user’s safety.

To test the accuracy of an App in determining the risk of falls in elderly women, 24 elderly women admitted to a hospital were evaluated by the TechOne App, regarding self-report of falls, by the clinical questionnaire (“TFQ”) and subjective motor evaluations by the questionnaire “TMPSE”. Then, in one faller and one non-faller volunteer, stabilometric variables were measured in the static bipedal posture by the inertial sensing algorithm “TBM”. The scores of the questionnaires were compared between fallers and non-fallers by the ANOVA test for independent measures and by the ability in discriminate fallers by the Area Under de Curve (AUC) of the ROC curve and traditional classification measures. The TechOne App demonstrated to be technically viable to obtain stabiliometric variables, demonstrating clear difference between one faller and one non-faller volunteer. The TFQ showed excellent metrics (Sensitivity: 90%; Specificity: 71.4%; Accuracy: 79.17%; AUC: 0.875) and difference between groups (p < 0.05). The TMPSE score showed no significant differences and presented lower classification metrics (Specificity: 64.3%; AUC: 0.654). It is concluded that TBM is potentially viable and the TFQ is accurate to predict falls.

The growing appreciation of pets has enabled us to improve the technologies to make a prosthetics for then. Amputations in dogs can be performed due to trauma, or neoplasms, and the animals may develop compensatory disturbances for the short or long term, that can lead to chronic pain. Prosthetics are devices that replace the absence of a limb or other part of the body. Its main objectives are to align the spine, decrease the overload of the weight in the remaining limbs, muscle control, and external mechanic system that can help to lead to functional independence of the patient. The goal of this paper is to develop a metatarsophalangeal prosthesis of a left pelvic limb of a dog. The steps were: medical evaluation for the use of a prosthesis by a veterinarian, confection of the negative and positive molds, confection of the device, adaptation process, and evaluation of results.

The purpose of this study was to analyze the agreement between muscle activations calculated using Static Optimization (SO) and experimental measurements from surface electromyography (EMG), applying different exponentials to the cost function, during the Bandal Chagui kick. Three-dimensional kinematics, of three kicks, from five black belt athletes, were analyzed. The fastest kick for each subject was processed using the freely available software OpenSim. The tools used were inverse kinematics, residual reduction algorithm (RRA) and SO. The waveforms, estimated with the SO, from eight muscles of the dominant lower limb were compared with surface EMG measurements in phase (P), magnitude (M) and global agreement (C) by equations in which a perfect agreement results in zero. A global agreement close to zero was found for the gluteus medius and maximus (C ≤ 0.12) using 4 as the exponential and for the biceps femoris, with 2 as exponential, the global agreement was good (C = 0.19).

Sonothrombolysis consists in a new treatment based on ultrasound to help to unblock arteries that may be blocked by a thrombus, helping in infarct treatment as a noninvasive method. Although it is a new method, it has shown great progress thorough recent years. Among the variety of applications of this technology, the Phased Array Ultrasound Technique (PAUT) can achieve a higher pressure with the same power using the focused beam concept. In this paper, this technique is analyzed as a tool for sonothrombolysis treatment and compared to other conventional techniques. The advantages of the phased array ultrasound technique are shown by wave simulation programs. After that, a project for an ultrasound device prototype is introduced. The project implementation and its characteristics are also explored herein.

This paper describes the development and characterization of a solenoid radiofrequency (RF) coil specifically designed for MRI acquisition of ex situ brain samples at 7 teslas. The coil was designed to maximize the filling factor of small brain samples, such as hippocampus and brainstem, providing optimum signal-to-noise ratio (SNR) when compared to a 32-channel volume head coil available. SNR measurements comparing the performance between the constructed solenoid and the available head coil have shown a gain of 4.8 times. As expected, field homogeneity achieved by the solenoid was found to be considerably worse when compared to the volume head coil. Nevertheless, the available region with high homogeneity provided by the solenoid showed to be enough to cover the whole sample and generate images free of RF inhomogeneity artifacts. The solenoid coil allowed the acquisition of high spatial resolution images of ex situ brainstem samples, making possible the discrimination between gray-white matters in the brainstem anatomy.

This paper evaluates a potential system to perform Medical Imaging dealing with electromagnetic waves at microwave frequency range. It aims at detect early breast cancer in a portable and low-cost solution instead of expensive and bulky equipment. An explanation about Microwave Imaging and Software-Defined Radio is presented. Employing GNU radio toolkit, a Radio Frequency communication was performed, whereby SNR close to 80 dB was achieved, showing that the proposed system is suitable for our project, paving the way for further work.

In this work we present the design, construction and characterization of a peristaltic pump for biological applications. The design considers the blood flow with the possibility in a future, to perform the simulation of cardiac pathologies. The system is based on a peristaltic pump (which emulates how the heart works), Teflon hoses and a blood mimic [2] with rheological properties similar to real blood. The phantom is able to simulate blood flow, as well as the ability to show variations in blood flow, according to the selected mode. The blood flow was validated with commercial Doppler equipment. This is the first version of the prototype and it can be modified and arranged for a correct functioning of the phantom, after the experimental evaluations.

The absence of interference by radio waves, due to the use the unlicensed light spectrum provided by light-emitting diodes (LEDs) sources, is one of the main advantages of visible light communication (VLC) systems in health classified areas. The robustness of a stable and reliable VLC system, for application in intensive care medical environments, is experimentally demonstrated in this paper. A proof-of-concept experimental setup is presented and the results described to confirm the performance of on-off keying (OOK) schemes based on Manchester coding. The experimental results show that the transmission, of real data provided by a patient monitoring equipment, over a VLC link of 1.5 m, was successfully achieved with the wide range of LED bias current between 10 and $$\approx 700$$ ≈ 700 mA.

Hemodialysis is a procedure responsible for performing the blood filtering function of a diseased kidney. During the hemodialysis process, the dialer responsible for filtering blood is reused after disinfecting its membrane, which process might leave residues that may be harmful to health. A disinfection of hemodialysis machines is performed with an acidic solution. This paper focuses on the development of a device that can detect harmful and unwanted substances present in the circuit of the patient. The equipment proposed in this research performs an automated dialer and patientline acid detection process that applies increased safety to the healthcare professional and prevents discomfort or damage that may be caused by peracetic acid residues to the patient.

Tendon injuries are among the most common orthopaedic problems with long-term disability as a frequent consequence due to its prolonged healing time. Thus, the study has investigated the effect a new fibrin sealant (FS) derived from the venom of crotalus durissus terrificus in tendon repair. Therefore, 12 animals (±185.8 g) from Wistar lineage, showed average weight ± 185.8 g. All animals received the partial transected tendons and then they were separated in two group a random way: Lesion group (GL) and fibrin sealant group (GS). Immediately after the tendon injuries, 9 µL of fibrin sealant was applicated in each transected tendon, in order to form a stable clot with a dense fibrin network. The methodology of edema analysis was made in three stages: before the partial transected tendons, 24 h after tendon injuries induction and after 21 days of fibrin sealant treatment. The quantification of collagen was by slide colored with picrosirius red. We applied the Kolmogorov–Smirnov test to verify the normality between the groups. For the comparison between the groups the Student’s teste was applied for parametric samples and Mann–Whitney test for non-parametric samples with significance level of p < 0.05. The results showed that there were not significant difference between the groups in the first 24 h before the lesion, but the fibrin sealant treatment for tendon lesion can be promote the reduction of edemas after 21 days. The fibrin sealant group showed similar collagen deposition with the injury group, but with the collagen fibers more organized. The results suggest that the fibrin sealant is effectiveness to treat tendon injuries.

Respiratory muscle weakness can be one of the aftereffects due to cervical or high thoracic spinal cord injury (SCI). This problem affects the organism's capacity to maintain the correct levels of oxygen, and the cough events start to be difficult to perform. Studies have demonstrated that the application of synchronized Transcutaneous Functional Electrical Stimulation (TFES) to the respiratory muscles, diaphragm and abdomen, enhanced their resistance and strength. So, this study aims to evaluate if electromyography (EMG) sensors positioned on the sternocleidomastoid (SCM), omohyoid (OM), and external oblique (EO) muscles can be used to help in automatic cough prediction for a future TFES synchronization system. Voluntary coughs of nineteen volunteers were recorded using three EMG sensors and their potential use in cough prediction was evaluated. Results show that EO muscle presents better results (55 ± 31.37 V) in amplitude variations compared to the other ones. However, it is still not possible to standardize one single muscle for prediction due to the variation of activation in each person. Also, the use of EMG sensors can contribute significantly to cough prediction systems considering the muscle response can be perceived well before the sound.

An integration involving power line communication (PLC) and visible light communication (VLC) technologies is experimentally investigated in this work, for data transmission in hospitals. This combination represents a promising solution in classified areas, where radio frequency wireless transmission is prohibitive due to interference in machinery used in certain medical services. This is also motivated by a physical layer transparency provided by the adoption of the orthogonal frequency division multiplexing (OFDM) in both technologies. Bit rates around 10 and 230 Mb/s measured after propagation through 21.7 m in downlink and uplink, respectively, show the suitability of the PLC technology as an alternative backbone to a central data monitoring. Moreover, a bit rate around 4.8 Mb/s can be achieved with the VLC system in a link of 2.0 m, with an error vector magnitude (EVM) of $$-24$$ - 24 dB, confirming the robustness of this integration.

The production of giant unilamellar vesicles (GUV) has been the subject of many studies due to its simplicity and to mimic essential complex functions of biological membranes. The precise control of the medium temperature and the electric field amplitude in saline solutions is crucial for the formation of GUV to be used in the analysis training protocols for biomedical applications. Herein, we propose two automatic temperature control methods and stability of the electric field amplitude in the saline solution. The control system is based on a microcontroller that uses pulse width modulation to control the actuation devices. Over time, the field amplitude stability was assessed through an applied electric field with a frequency of 500 Hz and a voltage amplitude of 600 mVrms. Two algorithms for controlling the field amplitude were analyzed: bang-bang and proportional-integral-derivative (PID). Their performance was evaluated in saline solutions kept at room temperature and 60 °C. The mean values of the field in the absence of control, with bang-bang control and PID control, showed differences compared to the initial value, 17%, 1%, and 0.3%, respectively. Based on findings, the PID protocol proved to be the most effective in maintaining field values over time.

Bioelectric signals are emanations from living biological systems and have their origin in various electrical potentials in cells. In this context, electrooculography (EOG) is defined as a specific biopotential is generated by the eye and eyelids’ muscular movement. Here, we are dedicated to developing a methodology and an appropriate environment to detect the human eye’s movement by acquiring bioelectric signals. The study was conducted in 40 healthy individuals using the 4/5 configuration consisting of four main electrodes and an additional fifth reference electrode. The methodology is following standards and guidelines for data acquisition of ECG signals. During the acquisition, the volunteer remains seated and with his head comfortably sustained on a support of a tailored Ganzfeld box. On the back wall of the box were fixed five light-emitting devices (LEDs) in the form of a plus sign symbol positioned at a distance opposed and at the center. The LEDs were turned-on or turned-off according to a pre-established sequence protocol synchronized with data acquisition while the volunteer performed eye movements. As a result, were obtained 18 samples of EOG signals per subject of 60 s. A dedicated algorithm was used to separate the data by group according to the established methodology.

Flexible square coils are widely applied in wearable devices, especially in wireless power transfer systems. Wearable biomedical sensors are solutions where the electronic circuits are embedded into the clothes, for long-term patient monitoring in homecare health. The determination of coil´s inductance in a situation of flexion is not trivial, and may involve complex equations. In this paper, an analysis of inductance in flexible square coil, using classical Neumann equation, is proposed. An approximation with decagonal coils was used to simplify the calculation. Two sigmoid curves were calculated for fitting with high correlation. The simplification presented an averaged error less than 4.1%. Finally, comparisons with practical data are done. This proposed procedure can help in the design of flexible coils applied in wearable biotelemetric devices.

This article presents the study and recommendation of a method to improve the observation, in laboratory experiments, using a microscope stereoscopic or stereomicroscope with chicken embryo chorioallantoic membranes (CAM). In these experiments, tumor cells are implanted in this CAM so that they will form a tumor during the embryo's development period. The number of neovessels that develop around the tumors are indicators of results on testing with antiangiogenic drugs. These studies require quantification of vascularization to compare the stimulating or inhibitory effects caused by different agents. The proposed method to improve the visualization of the vessels consists of a lighting chamber composed of three lighting rings, to accommodate the egg, for observation in a microscope. Each ring is composed of sets of 8–16 LEDs, with a temperature of color between 3000 and 5500 K, aligned, focusing on the regions above, central and below the egg. The method provided an improvement in the results as more details of the images were observed, when compared to the images obtained with the original illumination of the adopted microscope stereoscopic or stereomicroscope, model LEICA ZOOM™ 2000. Also, the proposed LED lighting avoids the heating irradiated by the original illumination, which may cause discomfort, dehydration and unnecessary movements of the embryo, besides reflection or glare on the exposed membranes and liquids of the egg, which may impairment the visualization. Qualitative evaluation of sample images demonstrated that subtle vessels stand out, thus allowing better results for further quantitative analysis of the CAM. The quantitative analysis of the images, using the vessel counting method based on a grid, resulted in a mean percentage difference counting of +56% vessels in relation to the counting with the original illumination of the microscope.

Neuropathic pain (NP) is related to the presence of hyperalgesia, allodynia and spontaneous pain, affecting 7–10% of the general population. Repetitive transcranial magnetic stimulation (rTMS) is being applied for NP relief especially in patients with refractory pain.Objective: As NP response to existing treatments is often insufficient, we aimed to develop a magnetic stimulator and customized coils and evaluate rTMS treatment over the nociceptive response of rats submitted to a NP model.Methods: The magnetic stimulator and the butterfly coils were developed in the Biomedical Engineering lab of Hospital de Clínicas de Porto Alegre. The device generated pulses with a 1 ms pulse width in a 1 Hz frequency. A total of 106 adult (60-days old) male Wistar rats were divided into 9 experimental groups: control (C), control plus sham rTMS (C + s.rTMS), control plus rTMS (C + rTMS), sham neuropathic pain (s.NP), sham neuropathic pain plus sham rTMS (s.NP + s.rTMS), sham neuropathic pain plus rTMS (s.NP + rTMS), neuropathic pain (NP), neuropathic pain + sham rTMS (NP + s.rTMS) and neuropathic pain plus rTMS (NP + rTMS). NP establishment was achieved 14 days after the surgery for chronic constriction injury (CCI) of the sciatic nerve, and rats were treated with daily 5-min sessions of rTMS for 8 consecutive days. Nociceptive behavior was assessed by von Frey and Hot Plate tests at baseline, after NP establishment and post-treatment.Results: The measurement of magnetic field intensity 2.5 mm and 5.0 mm from the coil center on the 90º axis showed 160 mT and 125 mT respectively. rTMS treatment promoted a partial reversal of the mechanical allodynia and a total reversal of the thermal hyperalgesia induced by CCI.Conclusions: We presume that low-frequency rTMS is a potential tool for NP treatment, possibly due to the modulation of plasticity and promotion of an analgesic effect.

Atrial Fibrillation (AF) is a supraventricular arrhythmia in which an irregularity in atrial electrical activity causes the atria to lose their ability to contract efficiently. This causes the heart to fail and is an increasingly legitimate risk factor for palpitations and clot formations that can cause stroke. Patients suffering from this cardiac pathophysiology require constant monitoring of their cardiac activity, requiring regular visits to the cardiologist or the use of constant cardiac monitors. To increase the quality of life of these patients, wearable devices can be used to remotely monitor and detect cardiac arrhythmias in real time. This work aims to do a scoping review on the use of wearable devices for the detection and monitoring of AF. To implement this process, a computational tool, StArt (State of the Art by Systematic Review), was used to assist the researcher in the application of this technique. A total of 1979 articles were selected at first; in the end, 10 articles were kept for further evaluation. The results of this review showed that, not only are new technologies being made to detect AF, but existing devices are being tested for their validity and feasibility in clinical settings. To test for device validity, a 12-lead ECG is the gold standard against which these existing or novel devices’ screening are compared to, being cited in more than half of the final ten articles as their reference standard. All in all, the studies showed great accuracy, with sensitivities being all in the 90th percentile, on average, and all articles concluded that the study of devices had various clinical benefits and were viable options for AF detection in the future.

With the advent of SARS-COV-2, industry and academy have been mobilizing themselves to find technical solutions to satisfy the high demand for hospital supplies. This work aims to study the manufacturing process by melting and depositing thermoplastic material (three-dimensional printing) to build a mechanical ventilator. We center the methodology of this work on the observation of good practices for the procedure of printing plastic parts for medical and hospital use, aiming to guarantee mechanical resistance and satisfy sanitary restrictions. At first, we studied materials for manufacturing parts for application in the medical-hospital environment. In a second moment, a study of the mechanical resistance of specimens for traction test was developed, based on the ASTM D638 standard, printed with different directions of material deposition and using different types of thermoplastics with potential use in medical systems such as PLA, ABS, and PETG. In a third moment the mechanism of a mechanical ventilator in Solidwork was created, this mechanism automated an AMBU using a rack and gear system, the properties of the PLA material (of the second moment) were applied to the gear (it is the most critical part of the mechanism) and the effects of torsion on the gear were simulated (stepper motor). Finally, a 3D printing mechanism was created. For the production of these specimens, we employed the Simplify 3d software. Optimized settings were suggested for the deposition of the thermoplastic material, considering a reduction in speed to 30 mm/s, a layer height of 0.100 mm, 100% filling, and a line overlap of 60% to avoid voids at the edges of the pieces, within order to increase the mechanical resistance. The observed results are satisfactory and are under the analyzed bibliography, indicating that adjustments in parameters and configurations of material deposition influence the mechanical strength of the parts.

The aim of this paper is to present a new ultrasound platform for medical imaging research, in which all the image formation, capture and emission parameters are user-defined. The requirement to be fully configurable was necessary to enable the evaluation of new signal processing and beamforming algorithms developed by researchers. Since it is a new equipment, different subsystems (synchronism, human–machine interface, platform configuration, image formation, hardware and mechanics) were designed and developed. The degree of flexibility required resulted in a large amount of configuration parameters to be described by the user. The JSON file format provided a well-structured and clear way to describe the different parameters. The hardware design is multi-board. The various functions of the platform are performed by the Synchronism, Multiplex, Tx and Rx boards, mounted in a rack that communicates with a PC. The transmitted beam and the receiver beamforming are generated and implemented in programmable hardware, using FPGAs. Some design techniques reduced the cost and development time, like the use of FPGAs in commercial modules. The RF signal is processed in a GPU using four pipelines that run sequentially to produce the images. First results using different configurations has proven the efficiency of the solution.

This paper presents the development of a one-dimensional force platform for the pedaling analysis in a bicycle using piezoelectric films. A 3D-printed insole was designed to accommodate an array of Polyvinylidene Fluoride films without changing the pedaling characteristic. The sensor’s positioning sought to cover the point of contact between the shoe and the pedal. An instrumentation amplifier, a charge amplifier and an anti-aliasing filter with a cutoff frequency of 20Hz composed the conditioning circuit. The system dynamic calibration was executed with the application of mechanical impulses to the sensors’ surface using an impact hammer of model 8206 by Brüel and Kjær, and a chassis model NI SCXI-1600 acquired the output signal. Hence, the experimental transfer functions were defined for each one of the 20 channels of the system. The maximum linearity error was 5.98% for the channel #4 of the right insole and 5.81% for the channel #7 of the left insole. A NI USB-6289 board acquired the data coming from the trials with a bicycle. In the collected data analysis, it was possible to define the pedaling phases by observing the sum of all channels for each insole. The average value for the maximum force applied on the right insole was 235.8 N, and the average value for the maximum force applied on the left insole was 223.2 N. It was possible to map the zones of greater and minor activation during the movement via a single channel analysis for each insole, being the regions of greatest activation located at the top of the medial forefoot region (right foot), and at the bottom of the lateral forefoot region (left side). The regions with the least activation are at the bottom of the medial forefoot region (at the end of the medial longitudinal arch) on both sides.

This paper presents the implementation of a soft sensor for hand-grasping force by the sEMG (Surface Electromyography) collect from 6 different muscles in the ventral regions of the forearm. This work is implemented in the envelope of the signal from sEMG by a low-pass filter with a cut frequency of $$3 {\text {Hz}}$$ 3 Hz , which maintains the information of the energy of the signal. An Artificial Neural Network (ANN) was applied for the regression of the force and was done an online application of the model as a soft sensor, and has as input the 6 channels of sEMG rectified and filtered. Four volunteers were tested to see the viability of the regression, all of them showed high $$R_{{\text {sq}}}$$ R sq for fitting the regression model, 0.99, 0.98, 0.98 and 0.97, respectively proving the capability of the application. The online performance demonstrated $$16.66 [{\text {N}}]$$ 16.66 [ N ] of root mean square error, approximately $$3.14\%$$ 3.14 % of a MVC (Maximal Voluntary Contraction) threshold of volunteer 01.

Transcranial Direct Current Stimulation (tDCS) has been the target of research in the search to understand its therapeutic effects on human health and the mechanisms by which these effects are mediated. The lack of standardization and the high cost of tDCS devices for clinical trials are some of the bottlenecks in the progress of tDCS research. The development of low-cost open-source devices, adaptable to research questions and that encourage innovation in the area are important. These devices can contribute to the understanding of tDCS mechanisms and effectiveness. Thus, this project presents a development of a tDCS prototype for clinical trials, consisting of hardware for electric stimulation, and a mobile app as a human–machine interface. The hardware is based on a direct current source and a microcontroller (ESP32), which communicates via Bluetooth® with the app. The mobile app was developed collaboratively with researchers. The built prototype had its performance evaluated through bench testing, showing a current production accuracy of 96.53%. It is expected that this project will facilitate access to tDCS devices to research groups that want to explore their effectiveness in most health conditions, following the methodological rigor of clinical trials.

Decubitus ulcers generate costs about 11.5 billion dollars per year in the EUA and cause many injuries such as pain, infections and deaths, totaling about 60 thousand deaths per year. Based on that, this paper presents the development of a bed pressure monitoring system, suited for everyday use to prevent pressure ulcers, that uses alarms to support the caregivers and health professionals to improve health conditions for patients. Instead of using units of sensors to build a sheet of sensors, the proposed solution was made with Velostat, a conductive material which is a carbon-impregnated polyolefin, this choice reduces the cost of the system, enabling access to patients in critical conditions in their homes or even in public hospitals. At this way, a reduced dimensions prototype was built using this conductive sheet which is pressure-sensitive and, as result, the tests demonstrate the functionality of the system, indicating peak pressure in real time on the patient’s skin on a mobile app.

Electroencephalography (EEG) has been the focus of research and advances for many years, yet there are several tasks to be explore and methods to be tested to improve analysis and classification. Event-Related Potential (ERP) is one of the brain responses measured with EEG, resulting from motor tasks usually are related to motor imagery or real movement. This study aims to analyze and classify event-related desynchronization (ERD) and event-related synchronization (ERS) occurred in tasks involving passive mobilization in Intensive Care Unit (ICU) sedated patients and non-sedated volunteers. Our main goal is to provide preliminary analysis and comparisons between sedated and non-sedated groups based on signal visualization and a classifier. Common Spatial Pattern filtering (CSP) and visual inspection of best band and time were used to verify signal and phenomena. From that, specific features (i.e., Root Mean Square, standard deviation, mean of Welch periodogram and differential entropy) were extracted based on time and frequency to apply a Linear Discriminant Analysis (LDA) classifier. Once the two Intensive Care Unit sedated patients and the two volunteers were analyzed, it was possible to observe the proposed phenomena. Mean accuracy in the best scenario and best person for each group (two people in each group) was found higher than 80 and 77% to sedated and non-sedated participants, respectively. Preliminary results, based on four participants (i.e., two sedated and two non-sedated patients), suggested lateralization in tasks performed with passive mobilization and provided accuracy comparable to previous studies involving motor tasks.

Patients admitted to Intensive Care Units (ICUs) may develop oral health problems, causing accumulation of dental biofilm, tongue coating and inflammation in periodontal tissues, considered microbial reservoirs of bacteria. Such problems are associated with hospital infections, in particular the increased risk of a respiratory infection known as mechanical ventilator-associated pneumonia (VAP). This specific oral health condition may be related to the lack of professional training in the ICUs, the absence of a participatory dental team in the clinical and educational context and the lack of specific and/or effective protocols. In this context, the present study aimed to verify the oral health condition of adult patients admitted to the intensive care unit of a public emergency hospital in Teresina-PI as well as the compliance with the recommendations of the standard operating procedure established by the Brazilian Association of Intensive Care Medicine (AMIB) regarding the use of the fluorescence technique for oral hygiene. The research was a descriptive, quantitative and observational study, and the research sample was made randomly among adult patients admitted to the ICU. The data collection occurred in two steps. The first involved a diagnosis of the presence of bacterial plaque in the oral cavity of patients hospitalized in the ICU using a fluorescence system, while the second consisted of a diagnosis by fluorescence made before and after oral hygiene with the application of the protocols recommended by AMIB. The results showed that the oral hygiene care performed in patients hospitalized in the ICU is deficient, with the absence of a standard hygiene protocol as well as a professional dental surgeon in the multidisciplinary team of the unit. Therefore, it is important to implement an oral hygiene protocol, according to AMIB, to prevent oral diseases, possible infections and worsening of the patients’ systemic condition.

Photobiomodulation is the emission of low intensity light to locally induce cells to equilibrium. One of its possible applications is for skin wound healing. However, any such solution must be non-contact because on the contrary it can cause pain and make the treatment unfeasible. Here we propose a device capable of emitting red light through LEDs to treat this type of injury in a non-contact way. In addition to assessing the optimal irradiation distance and estimating a maximum area of homogeneous coverage, we compared seven different configurations to assess the temperature stability during the treatment application. We tried two values of power density for the emission (50 $${\text {mW/cm}}^ {2}$$ mW/cm 2 and 60 $${\text {mW/cm}}^ {2}$$ mW/cm 2 ) and two distance measurements (5 and 7 $${\text {cm}}$$ cm ) between LED boards and a temperature sensor, over a 10-min period. As a result of the optimal distance experiment, the 5 cm distance was used in the following two experiments, where at this distance it is possible to carry out applications covering a homogeneous area of up to 323.95 $${\text {cm}}^{2}$$ cm 2 . In the temperature fluctuation experiment, we found that, although some configurations have less stability than the others, none of them compromises the efficiency of the treatment.

Endotracheal Suctioning is a clinical resource commonly used for the bronchial hygiene of patients under artificial ventilation. This work aims to propose a new procedure to avoid damage to the patient during this process. Considering the importance of assessing the impact of the mechanical ventilation-suctioning interaction on the respiratory system, one of the objectives of this work is to validate a computational model of a closed tracheal suctioning system. For that, the pressures, obtained by the model, were compared to those resulting from aspiration in a physical lung model. Combinations of catheter and orotracheal tube sizes, as well as ventilatory and suctioning pressures, were used. The difference between the alveolar pressures obtained with the computational and physical models was not greater than 0.3 cmH2O; with the correlation between the signals higher than 0.999. Therefore, the computational model was considered adequate for the alveolar mechanical representation in the proposed condition. With the validated digital model and aiming to obtain less loss of volume and alveolar pressure of the patient model, an intermittent suctioning with parameters of 4 patients was implemented (one healthy, one with a restrictive disease, one with obstructive disease and one critical with both disorders). When comparing normal and intermittent suctioning, there was an improvement in the mean alveolar pressure and a decrease in maximum pressure drop during suctioning in patients.

A first prototype version was developed for testing the resistance in sunglasses frames, according to NBR ISO 12311:2018, which can also be used for prescription glasses. It tests the durability of the frame by the act of placing and removing the glasses from the face by the user, ensuring the quality and safety of glasses sold to consumers. A mechanical system was designed, consisting of a nose simulator and fixing edges for one of the glasses’ temples, which simulates the side that is fixed behind the ear; and an electronic rotation system—40 rpm—for testing the other temple (simulation of the side that will be removed from the face) and frames have been tested. Tests were performed on 30 samples, out of which 04 were non-compliant with ISO and for only one of them the motor’s torque was not adequate to perform the test. In addition, 5 samples moved away from the “nose” during the test, not comprising the test, but suggesting a more efficient design. The prototype will be revised for proper testing of frames with larger and smaller dimensions than the standard as well as the engine will be re-designed to test samples with less flexible frames. Also, international equipment of the market is discussed, pointing out inadequacy in relation to the requirements of the standard. This research was financially supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)—process number 2018/16275-2.

The present work aims to make a proof of concept comparing mechanical tests in a commercial model of airway stent (HCPA-1) versus experimental and virtual simulation mechanical tests using finite elements in a dimensionally similar stent made by a 3D printer in flexible non-biocompatible material. The material of the 3D printed stent was hyperelastically characterized from experimental mechanical tests on samples that allowed calculating the constitutive constants for the hyperelastic models. Virtual simulations of mechanical tests using finite element analysis in the ANSYS software with the available hyperelastic models were compared with the experimental tests, obtaining the precision of the hyperelastic models in the material used to print the stent. A cough-like mechanical test was performed experimentally on HCPA-1 and 3D printed stents simulating a critical condition of use. The results were compared with a virtual simulation using the hyperelastic models obtaining precision that varied from 2.5 to 280% depending on the hyperelastic model used. The work shows that it is possible to obtain virtually the mechanical response of an airway stent using finite elements. Making it possible to minimize the time and financial investment needed to evaluate the research and development of new materials, geometries or customized models based on medical images using the 3D printing technique. Flexible and biocompatible materials for the 3D printer should emerge in the future. Allowing 3D printing of implantable airway stents in patients.

Electromyography (EMG) is the study of the muscular functions through the detection of the electrical signal produced by the muscles. It is used to investigate several motor disorders such as Parkinson’s disease, multiple sclerosis, and spinal cord injuries. Electromyographic signals can also be used to develop assistive technologies devices, improving the life quality of certain patients. Such devices require a small size, wearable, active electromyographic electrode. Programmable System on Chip microcontrollers includes analogic and digital elements that allow integrating most of the electromyographic signal acquisition process in a single integrated circuit. However, we must verify if the internal noise level of these devices are compatible with this application. This work describes a surface electromyographic acquisition system implemented as an active electrode in a single Programmable System on Chip. Experiments were conducted to evaluate the internal noise of the developed system and verify if it’s compatible with electromyographic signal requirements.

In this paper, we present the implementation of a reconfigurable FPGA-based system for transferring raw ultrasound data using Gigabit Ethernet interface to perform and evaluate the digital signal processing steps according to the Delay-and-Sum (DAS) beamforming method for B-mode imaging, in order to reduce the transfer and computing time. The proposed system consists of two Terasic FPGA development boards and a computer with the Matlab software. The first FPGA board is used for assembling and transmitting data packets with ultrasonic information via Ethernet protocol. The second FPGA board receives the data packets and performs the back-end digital signal processing. The resulting data are transferred to the PC, through a USB port, for scan conversion and image display. The experiments were performed using RF data from an ultrasound phantom for active apertures of 8 and 32 elements. The performance of the proposed algorithm was evaluated by computing the normalized mean square error (NRMSE), contrast ratio (CR) and the contrast-to-noise ratio (CNR) of the reconstructed B-mode images. The analysis of the reconstructed images was performed by comparing the results from the reference Matlab script to results from the Simulink model and the FPGA experimental architecture. The overall processing time was reduced significantly to less than 10 s. Both the qualitative and quantitative analysis results of the generated images indicate that the Simulink and FPGA responses are in excellent agreement with the reference Matlab model.

Objective: The present study aimed to analyze, using accelerometry, movement patterns of activities performed during physical therapy rehabilitation in order to develop a software for physical therapy monitoring. The system is able to receive the accelerometry data through Bluetooth protocol, perform the processing to generate graphs in real time and store them in text files, in order to provide data for further analysis. Methods: This is an experimental, descriptive, cross-sectional work, with sample for convenience. The study was approved by the Research Ethics Committee (CEP) involving human beings from the Health Sciences Center of the Federal University of Pernambuco (CCS/UFPE) obtained the Advice Number: 3540474. In the study 10 healthy subjects aged between 20 and 40 years participated. For the development of the system was used Processing, which is an open source programming language based on JAVA. Processing contains computational tools ideal for the development of user interfaces as well as tools for processing and manipulating data from computer input and output devices. For the testing phase, the activities of sit/stand and walk were performed. The accelerometer was positioned on the lumbar spine of the participants. Results and discussion: According to the tests conducted the X and Z axes of the accelerometer were selected for analysis and these two satisfactory to identify the movements of sit/stand and walk of the volunteers. In this way, a limit value is determined that differentiates the sitting from the raised state. Thus, it was considered that the Z axis corresponds to the activity of sitting/getting up, whereas the X axis corresponds to the activity of walking. Conclusion: It was concluded in this study that the software developed is able to detect and monitor patterns of body movements through the oscillations captured by the accelerometers, suggesting that it can assist health professionals both in the assessment and in the physical therapy rehabilitation.

The B-mode ultrasound imaging represents one of the main imaging methods in medical diagnosis. To improve the quality of generated images, new approaches and techniques for digital signal processing based on hardware and software platforms are being introduced nowadays. This article shows the implementation and evaluation of digital signal processing algorithms on the Raspberry Pi using Python programming language for B-mode image reconstruction. The proposed steps include digital filtering, focusing delay, coherent summation, demodulation with envelope detection, and logarithmic compression. To validate the implemented algorithm, 12-bit sampled data with a frequency of 40 MHz were used. Qualitative and quantitative analyses using the Normalized Root Mean Squared Error (NRMSE) and the Normalized Residual Sum of Squares (NRSS) cost functions show results compatible with the reference model in Matlab and validated in previous studies. All NRMSE results were less than 10% and NRSS results were close to zero, indicating excellent agreement with the reference Matlab model.

The absence of systems that allow greater security in access control in healthcare environments is a serious problem faced by health institutions. This fact results in losses of both economical and operational nature, since the activities involved on provision of medical services performed by professionals are significantly impacted directly or indirectly. Therefore, it’s important to manage the access control of people and equipments in healthcare environments. For this to happen efficiently, systems that implement such management with redundant security routines appear as good alternatives. In this sense, this paper proposes a system that performs access control in healthcare environments, capable of managing the movement of people and equipments, allowing to know, at any time, an approximated indoor-location of each equipment or person. For this type of communication, several consolidated technologies are used, such as RFID (Radio-Frequency Identification) and Beacons (Bluetooth). The purpose of this paper is to discuss the hardware and software modules, in addition to present a graphical interface, with connectivity options for remote management through IoT (Internet of Things) resources.

Cardiovascular diseases are the leading cause of death globally. The increase in chronic diseases, such as Diabetes Mellitus and hypertensive heart disease, added to the ageing population, brings in risk factors that increase these statistics. In this scenario, studies related to these diseases are fundamental for the prevention of deaths and for improvements in quality of life. For this purpose, a cardiac monitor was constructed using a piezoelectric transducer as the sensor. The signal was conditioned using Rail-to-Rail amplifiers and digitized by a PIC microcontroller. A computer controls and receives data from the microcontroller through an interface developed on Qt. When data is received, the application presents a seismocardiogram (SCG) waveform on a real-time chart, allowing the user to save data to a file and estimate the heart rate. The developed software also applies a digital filter to reduce interferences in frequencies above 55 Hz. Recorded data were verified using MatLab®. The characteristic points of the SCG were identified in the graphs presented on interface.

The Pelvic Floor Muscle (PFM) dysfunction affects about 50% of women and strengthening the PFM prevents and minimizes disorders such as hypotonia. Facing the need to strengthen the PFM, an intravaginal transducer was developed to capture the PFM electrical activity and use a game with a smartphone, using the Bluetooth protocol, allowing the user to have easy interaction and visual feedback of the PFM contraction. The developed transducer was positioned in the intracavitary region of the volunteer’s vagina, in order to acquire the PFM contraction signal, identified by the analysis of the electromyography (EMG) record. The transducer has its own EMG amplification system and a wireless communication system in a flexible casing. The volunteers were instructed to insert the transducer and perform the contractions and relaxation proposed during the game, which has a scoring system for each stage and measures EMG’s amplitude in real time. The use of the transducer was assessed at end of the tests, using a form, where the volunteers could also give suggestions for improvements in terms of use and comfort of the transducer. The evaluation reported that the transducer is easy to use and handle. Regarding the EMG analysis, the tracing was considered normal, without any interference. The transducer had similar responses for both volunteers with the same amplifier gain. However, the transducer is an invasive instrument for PFM rehabilitation, so it’s necessary to identify the patient according to the parameters weight, height, age and the proper positioning of the transducer in the vaginal canal, to improve the EMG signal capture in the training of muscle fibers for treatment in urogynecological physiotherapy.

Walking tests are widely used to evaluate therapeutic options in several patients, including pulmonary and cardiac patients, as they demonstrate functional capacity and possible clinical prognosis. Among the therapeutic options, exercises can be performed in terrestrial and aquatic environments, with the purpose of preventing and promoting health. The objective was to develop an integrated device for the acquisition and monitoring of hemodynamic parameters in terrestrial and aquatic environments during a walk test. It is a pilot study in three stages: device development; application and validation; and data analysis. A device for the acquisition and monitoring of hemodynamic parameters was developed, with the visualization of the sensor variables simultaneously in an LCD display. The step consisted in the validation and application of the instrument by the author herself, where a 6-min walk test was carried out on the ground and in the water. The last step was the analysis and interpretation of the data. With the application of the equipment, it was possible to identify hemodynamic variables in both environments through a walk test, in addition to data visualization and real-time transmission via Bluetooth protocol. The device proved to be easy to apply for monitoring hemodynamic parameters in terrestrial and aquatic environments, presenting good visibility to the health professional, assisting in decision making about the continuity of the conduct. The device becomes applicable in several environments because it is a portable tool and easy to handle.

Sound communication is the way animals use to exchange information, attack and defend themselves and also one of the ways the scientists can use to locate them. Passive sonar uses sounds from the environment to count things, locate things or trace trajectories. It can be used to find a gun shooter in a crowd or count the number of penguins in a beach or anything that makes noise in a shine or dark place. This paper presents a simple circuit capable of emulate a territorial sound of the Amphibian Scinax tymbamirim, based on Arduino board and the sound recorded previously in the animal habitat and an analysis that makes it possible to say that the sound produced is very similar to the recorded sound of the studied species.

The Brazilian Universal Neonatal Hearing Screening Program (TANU) aims to detect hearing loss in newborns. TANU is mandatory in Brazil since the Federal Act 12.303 published in 2010. Otoacoustic Emissions (OAE) is an objective and non-invasive screening method recommended by international organizations. Despite its well-known significance and strong local demand, there is still no Brazilian manufacturers for this type of equipment. This work describes the initial efforts for the development and production of OAE devices: a system for generating calibrated sound signals, such as like clicks, pure tones, and white noise, which meets the entire frequency range and intensities observed in TEOAE and DPOAE exams. The proposed system aims to be a reference for adjustment and calibration of probe microphones.

New ventilator designs in response to the pandemic would benefit from flow and volume measurements. This work compares approaches to calibrate a pneumotachograph (PTC) with either a polynomial or a non-polynomial mapping function. Bidirectional 3-L manual strokes with a syringe provided fixed-volume digitized segments of signal spanning the range of flow measurement of a 4-orifice PTC. Voltage-to-flow calibration functions, either polynomial or based on an additive square root term, were optimized in the sense of least squared errors between estimated and known volume per stroke, for each direction, inspiratory and expiratory. Calibrations with a regularizing penalization in the objective function, aiming at removing local extrema (maxima/minima) of the calibration curves within the usage range, were compared to the non-regularized versions. Regularized polynomial (3rd to 5th degrees) yielded relative errors on volume from 3.56 to 7.17%, whereas for standard (non-regularized) models the errors ranged from 0.81 to 1.68%; errors with square-root-based curves were an order of magnitude smaller. Although regularization worsened error performance, on the other hand it avoided implausible curve shapes. Robustness, convergence properties, computational and practical matters and requirements for field operation are issues to be probed further.

Population aging is a global reality, which can be characterized by morphological, psychological and functional changes. With the limitations resulting from the aging state, changes can occur in the performance of activities of daily living, such as decreased muscle strength, reduced bone mass, loss of flexibility and decreased capacity of the sensory system. Physiotherapy actively assists in the health promotion and prevention process, reducing the effects of the aging and improving the life quality. This paper has the objective of develop a movement monitoring device to assist in the rehabilitation of elderly people. The accelerometers or motion sensors, store data for long periods of time, providing information about the movement activities of the subjects over a desired period. These sensors are a useful tool in the assessment of physical activity. Through the data of accelerometer, it is possible to evaluate all type of physical activities. This is a pilot study composed by three steps: development, validation and application of the instrument. For the application and validation of this study, it was used a protocol of exercises, in order to capture the variations of the X, Y and Z axes of the accelerometers in each exercise. In the study, it was possible to identify the movements during the performance of the proposed protocol. Through he accelerometers position and the varying of his axes, it was possible to classify the exercises according to the number of repetitions and the time spent performing the exercise. In addition, it was possible to monitor remotely in real time by a physiotherapist. It is concluded that this device can assist in the management of elderly patients, assisting the health professional during the rehabilitation process.

The application of ultraviolet (UV) mostly UVC to food safety has gained attention in recent years as a potential alternative to chemical and thermal disinfection methods mostly due to the movement that happens worldwide towards the consumption of organic food from small producers. The objective of this work was to present a methodology to disinfect eggs using ultraviolet radiation in an equipment made with germicidal light for aquaria and commercially available materials at low cost. To disinfect the eggs, a box of galvanized material (40 × 20 × 25 cm) was built, with two ultraviolet lamps (253.7 nm; P = 8 W), 28.7 cm long, positioned above and below a grid made of nylon wire for positioning the eggs without blocking the light. The lamps were connected in a parallel circuit, which allows the switch to be activated and the two lamps to be switched on synchronously. To evaluate microbial reduction, the Salmonella sp survival fractions of 80 eggs collected from small rural producers in the city of Votuporanga were quantified, before and after exposure to UV light for 1 min, with an energy density of 0.208 J/cm2 and a power density of 3.4 mW/cm2. In the tested parameters, there was a reduction of approximately 1 log of microorganisms. Therefore, we can conclude that ultraviolet light is a possible technology to be applied to decontaminate eggs contaminated with Salmonella sp, which may contribute to the reduction of foodborne diseases.

In the interventional medical procedure, the medical team is subject to high exposure to scattered radiation when compared to other occupational groups that work with X-rays. The dose limits accumulated on the lens deserve attention to avoid a relative risk of developing a cataract after being absorbed by the eye lens. The objective of this work is to develop a system that allows estimating the dose accumulated in real-time in the lens of the eye received by the physician during the interventional procedure and indicate means of its protection against ionizing radiation. Dose rates were collected by the ionization chamber at 166 cm about the ground level, with distances of the main beam at 19, 38, 57, 76, and 152 cm, around the fluoroscopy. The estimated doses were visualized in real-time through a display showing the intensities of the accumulated doses. To test the performance of the system, we used an adult phantom with a size of 30 × 30 × 22 cm to measure the dose estimate in real-time in the region of the lens of the eyes simulating an interventionist procedure, we irradiate for 20 min, and the results of the estimates about X-ray beam distances were 220.6, 159.3, 110.3, 78.4 and 22.1 μSv per procedure and unshielded, respectively for those distances. The validation of the measurements was consistent in p-value 0.05 < p-value < 0.025. For the radiologist, the doses checked annually for 110 procedures in the usual position may be reduced from 17.5 from 38 cm to 12.1 mSv/years distant from 57 cm of the beam, well below the ICRP recommendations. The estimated dose in real-time helps the interventionist physician optimize their exposure to scattered radiation during the procedure, allowing them to enhance personal protection and reduce occupational dose in the of the eyes.

In recent years, the Internet of Things (IoT) has emerged as a major computing paradigm leading the development of new architectures for collecting, processing and store data. Among several concepts associated with IoT, we highlight the wearable computing, which allows users to interact with devices attached to the body. In this context, a large amount of human body signals can be acquired by using sensors connected to an embedded system, such as the Electrocardiogram (ECG) signal, which is widely used in medical diagnoses of heart diseases. Moreover, there is a huge interest on the maintaining of ECG samples to accomplish disease recognition by using different techniques that require a large database. Here we propose an architecture for ECG data acquisition, storage and visualization with a low cost and energy efficient embedded device. The proposed ECG reader with IoT architecture, which is a portable device with at least 40 h of autonomy, is able to collect data with sampling frequency from 125 Hz to 1 kHz and store up to 60 s of data samples in cloud server.

Cardiovascular diseases are the leading cause of deaths worldwide, causing more than 15.2 million deaths in 2016 alone. Thus, the need for intervention is clear so that these worrying numbers can be reversed. In this sense, a collective effort is needed in the areas of research and development of treatments for these cardiopathies. The purpose of this work is to develop a microcontrolled didactic bench that reproduces the behavior of the human circulatory system (HCS). The prototype will be able to elucidate the concepts involved in the dynamics of the flow and blood pressure of the systemic circulation. The basic elements that constitute the bench are a reservoir, a compliance chamber, a hydraulic piston pump driven by a direct current motor and a gate valve. All actuator elements and sensors are interconnected by a control system that can be accessed by a computer. The hydraulic circuit is based on the Windkessel model, which explains the transformation of the pulsatile flow of the heart into a virtually constant flow. The bench is capable of simulating scenarios of this phenomenon with parametric pressure variations between 40 and 210 mmHg and heart rate from 70 to 100 bpm. After the development of the bench, it was subjected to tests with fixed values of ejection volume and engine rotation for hypotension, normotension and hypertension, according to the norm ISO 5840-3:2013. The experimental data obtained from the bench were compared to the values ​​of the systolic and diastolic pressure ranges reported in the literature.

Ideally, the power output of electrosurgery units must be kept constant during its utilization despite the many differences in the resistance of tissues and the anatomic features of the patients being operated on. The aim of this paper is to present a method of designing the control stage of a high frequency electrosurgery equipment considering the adequate choice of passive components to reduce the variation of the power source voltage. The design focused on the automatic regulation of the average power output. The results obtained demonstrate that by using a simulation approach it is possible to predict the response of the electrosurgery unit output as a means to better regulate it.

This paper presents a system modeling for radar application in breast cancer detection. Near Field considerations are included in a high-level model to perform radio frequency system simulations. The proposed system is evaluated in order to provide the propagation losses due to attenuation in different breast tissues for a given set of transceiver parameters. Simulation results are presented in order to validate the system. A higher than 120 dB dynamic range can be pointed for a worst case scenario considering the breast with innermost tumor at 10 GHz frequency.

Several neuropathies of the peripheral nervous system (PNS) cause sensory dysfunction, leading to information distortion or even sensory loss. For instance, Diabetes nerve-damaging process leads to progressive loss of sensation, which indicates that an early intervention could reduce its effects. Among available exams, electrical stimulation can provide quantitative metrics as current perception threshold (CPT) and reaction time (RT), which would serve as a screening tool for assessing the disease’s evolution and differentiate the affected nerve fibers. We aim at developing a new multichannel hardware for the electrical stimulation system EE $$_{L}$$ L S, which would allow it to overcome limitations of the Neurometer and NeuroStim systems. We employ the Howland current-source topology combined with a bootstrapping power supply scheme to simplify the circuit design, reducing power stages and the number of required power rails. The new hardware presents high output linearity and stable load regulation when tested at frequencies (ranging from 1 Hz to 3 kHz). It can generate current stimulus of up to 8.63 mA with 4.51 $$\upmu $$ μ A resolution, showing total harmonic distortion (THD) inferior to 1 $$\%$$ % . When compared with NeuroStim and Neurometer, EE $$_{L}$$ L S presented similar or superior characteristics in term of stimulus generation (amplitude, frequency, bandwidth, linearity, and THD). Moreover, it presents two stimulation channels for the support of new exam protocols as, e.g., a two-point discrimination test. Therefore, EE $$_{L}$$ L S can be used for all the exams performed by its competitors (Neurometer and NeuroStim), adding new features to perform different exams.

Autism is a neurodevelopmental disorder that affects one in every a hundred sixty children in the world, according to the Pan American Health Organization. Interventions in multi-sensory environments are able to stimulate communication and social behavior. Thus, skills training programs and the behavioral treatment performed in this environment reduces the psychosocial impact of the disorder. Moreover, it gives to specialists tools for exploring personalized analyses for different groups of individuals and their levels of autism. Therefore, this study purposes the development of a multi-sensorial environment integrated to a multimedia software that deepens the experience of patients into different thematic scenarios configured by a specialist. It aims to optimize the time spent in clinical sessions used for evaluate various aspects of the treatment, provide resources for achieving the needs of patients and reduce costs during the medical supervision.

A fuzzy system for identifying pregnancy with a risk of maternal death is proposed in this paper. The system aims at identifying a high risk of maternal death, be it during pregnancy, or within 42 h after childbirth. The maternal age, number of prenatal appointments, and previous number of children/childbirth correspond to the input linguistic variables used to compute the risk of maternal death. The proposed approach employs the Mamdani inference system to represent the uncertainty and imprecision concerning the sort of diagnosing variables. Results demonstrate that the non-invasive system can be used by different health professionals, including in a screening process for pregnancy, thus avoiding maternal deaths.

Considering the great demand for aesthetic treatments in the dental hard tissues, the wide availability of whitening gels and light sources, as well as the concern with the harmful effects that the increase in temperature can bring to biological tissues, this study verified the changes in temperature of dental enamel, root dentin and pulp chamber during the in-office tooth whitening procedure with different light sources and whitening gels. Sixty recently-extracted lower human incisor teeth were prepared and randomly distributed among six experimental groups for treatments: G1-red whitening gel without light; G2-green gel without light; G3-red gel and exposed to blue LED light; G4-red gel and exposed to green LED light; G5-green gel and exposed to blue LED lighting; G6-green gel and exposed to red laser light. During the treatments, as well as one minute after finishing them, the pulp and surface temperature variations of the enamel and root dentin were monitored using four thermocouples. The pulp temperature changes were 0.3 °C (G1), 0.8 °C (G2), 1.8 ± 0.5 °C (G3), 1.9 ± 0.5 °C (G4), 3.35 ± 0.6 °C (G5), 0.34 ± 0.1 °C (G6). The temperature differences at the interface between gel and enamel were 0.3 °C (G1), 0.9 °C (G2), 4.42 ± 0.9 °C (G3), 4.9 ± 1.1 °C (G4), 4.7 ± 1.1 °C (G5) and 1.5 ± 0.2 °C (G6). The root surface temperature differences were 0.3 °C (G1), 0.6 °C (G2), 3.05 ± 0.87 °C (G3), 2.6 ± 0.96 °C (G4), 3.8 ± 0.27 °C (G5) and 0.30 ± 0.1 °C (G6) and the temperature differences on the enamel side were 0.25 °C (G1), 0.46 °C (G2), 3.2 ± 0.7 °C (G3), 2.97 ± 0.6 °C (G4), 5.13 ± 1.2 °C (G5) and 0.70 ± 0.25 °C (G6). None of the configurations of the experimental groups causes permanent damage to the dental tissues, however the combination of green gel + blue LED should be avoided, since it is the one that promotes greater temperature increases in these tissues.

Wound is the interruption of tissue continuity, caused by physical, chemical, mechanical trauma or triggered by a clinical condition, which triggers the fronts of organic defense. The body reacts to the installation of the wounds by initiating the healing process, however, these events may fail due comorbidities may be impair the healing response, resulting in a chronic wound. LED, light-emitting diode, have been successfully used as adjunctive therapies for stimulating skin wound healing however, the parameters used in low-cost equipment have not yet been studied yet. This study aims to evaluate the efficiency of a red LED light therapy equipment on wound healing in rats. The project was approved at CEUA/UESPI under protocol 0298/2019. Two experimental groups were delimited, one treated with LED and one control group. The animals were anesthetized and an area of 2 cm2 was cut with a skin punch. The treatment was performed for a period of 14 days, in which the regression of the wound was evaluated using the Image J program. When comparing the 14-day regression percentage between the LED treated group and the untreated group, it was observed that there was a significant difference in the regression percentage, being p < 0.05, in which the group treated with LED presented a higher regression percentage than the untreated. LED photobiomodulation therapy has been widely used demonstrating success in the regeneration of lesions by promoting photobiological effects that stimulate this process. This study showed that the low-cost red LED light therapy equipment resulted in faster healing process of the wounds, favoring the reepithelization and recovery of skin integrity.

Multipurpose fluoroscopy systems can be used as a remotely controlled system, or as a system for performing simple interventional procedures. Barium meal, or upper gastrointestinal studies, using fluoroscopy, is widely used for gastroesophageal reflux disease diagnostic in children and required professionals to stay inside the examination room for pediatric patient positioning and immobilization during the procedure. In such a situation the radiation exposure of professionals is an issue. The present study had as main goal to estimate the dose received by the professionals involved in pediatric upper gastrointestinal series. The polyethylene mannequin filled with water were used to simulate the patient’s body and another assistant. The equipment used to measure dose rate was a parallel plate ionization chamber calibrated with accuracy of 1.8%. The dose values in one examination are somewhat smaller but comparable with typical patient doses in chest radiography. The annual effective dose may exceed the limit in the case of hundreds of procedures. The contribution of the radiographic images may reach 30%.

In view of the growing spread of antibiotic resistant bacteria causing high morbidity and mortality, it is essential to develop compounds that are more efficient than those currently on the market. Maleimide derivatives, due to their chemical structure, have biological activity capable of deactivating enzymes and inhibiting the metabolic pathway of these bacteria and fungi. They have high selectivity and are new excellent antimicrobials. In this scenario, the objective of this work was to synthesize, characterize and verify the existence of bactericidal activity of two derivatives of maleimides, 4-vinyl-phenyl-maleimide and Cl-phenyl- maleimide. For this, the structures of the two compounds were characterized by High Resolution Mass Spectrometry (HRMS), Infrared (IR) and Nuclear Magnetic Resonance (NMR) 1H. Both compounds showed a double bond in the maleimide ring, essential for the inhibition of enzymes present in bacteria. The disk diffusion test to determine the bactericidal activity of the compounds, was carried out against the microorganisms: S. Aureus (Staphylococcus Aureus)—Gram positive, Monocytosis Lister—Gram positive, Escherichia Coli Enteropathogenic (EPEC)—Gram negative and Pseudomones Aureginosas—Gram negative. Compounds derived from maleimide obtain greater biological activity in Gram positive microorganisms, as evidenced by the inhibition halo in the diffusion test. The compounds proved to be active in the face of the disk diffusion test, indicating new permeability, selectivity and mechanistic studies, as well as possible applications of them as bactericidal agents.

This work presents a review about research published from the last five months (January–May 2020) about technologies used during the pandemic to fight the disease caused by the SARS-CoV-2 virus, termed COVID-19. Through an analysis of these studies, Telemedicine was considered as a viable option to decrease the dissemination of the virus and identify infected people. However, to implant Telemedicine worldwide, it is necessary a fast and reliable way to transfer of large amounts of data, such as the new fifth generation of mobile communications (5G). Thus, new concepts as Internet of Medical Things (IoMT) and the Electronic Health (e-Health) can be used, which have the necessary structures and tools for fast communication, with high-resolution, between patients and health professionals.

Cortisol is a steroid hormone that has an important function in the regulation of many physiological and pathological processes, while its quantification in biological fluids may contribute to the diagnosis of numerous diseases. The objective of this study is to verify the use of paper spray mass spectrometry (PS-MS) to evaluate the levels of cortisol in artificial saliva. Therefore, mass spectra in the range of 100–800 m/z were acquired using a Thermo Fisher Scientific LCQ FLEET equipment equipped with a low-resolution Ion Trap mass analyzer. The presence of cortisol in artificial saliva samples was evaluated by the presence of ions 363, 385, 725 and 747 m/z, which are related to the cortisol molecule. The spectra of saliva with cortisol addition shows the presence of ions attributed to the presence of cortisol at different m/z ratios, which are not present in the spectra of pure saliva, pointing out the potential of these ions for monitoring cortisol levels. The Principal component analysis (PCA) showed groups of samples with and without cortisol addition. The loading plot explains the groups formed by the differences between m/z associated to cortisol molecule, confirming PCA analysis as a powerful qualitative method to assess cortisol levels in saliva. Finally, the ions selected to discriminate the groups formed in the PCA, named 363, 385 and 747 m/z, were suggested as markers for determining cortisol levels in saliva samples. The PS-MS showed to an efficient and promising technique to the determination of real-time salivary cortisol levels without using any sample preparation step. From a volume of only 5.0 µL of sample, placed directly on the sampler equipment, it was possible to obtain an identification of cortisol by analyzing the mass spectrum in approximately 45 s.

Tinnitus is an irritating sensation of hearing a sound when no external sound is present, even interfering with the quality of life of its patients. Its increasing and high prevalence has reached millions of people. Fractal sounds are musical nuances with combined and semi predictable connections, generated by recursive procedures. This study presents a possible alternative treatment through the use of fractal sound, without sound amplification, in the relief of tinnitus, for a population of medium and low income, who do not have access to hearing aids of individual sound amplification—hearing aids. The study included 32 individuals, of genders, different ages, complaining of tinnitus, with sensorineural hearing loss, up to 60 dB. The project was approved by CEP-UTFPR. The research participant performed anamnesis, meatoscopy, pure tone audiometry, logoaudiometry, immittanciometry, acuphenometry and answered the questionnaire Tinnitus Handicap Inventory—THI and numerical scale at the beginning and at the end of the study. The fractal sound was heard through the participants’ own cell phones, with headphones provided by the cell phone manufacturer, for three months, for one hour daily. The type of tinnitus found was high pitch, with an ave-rage of 5673.5 Hz. According to THI, the severity of tinnitus that predominated most was the moderate degree at the beginning of the study and the mild degree at the end of it. The THI showed a significant difference in the functional scale, emotional scale, and catastrophic scale and also in the final total score of the questionnaire. There was a statistically significant difference in the initial and final averages of the numerical scale, in the level of awareness and in the level of discomfort with tinnitus.

Atrial fibrillation (AF) is a cardiac arrhythmia that affects around 33 million people worldwide. A standard form of treatment for AF is cardiac ablation with the radiofrequency catheter (RFCA). RFCA generates heat through the ablation electrode, and this process can cause severe lesions in the atrial and esophageal tissues. This work presents a two-dimensional computational model that uses geometry and boundary conditions that approximate cardiac ablation conditions with a non-irrigated catheter. The paper’s objective is to simulate the RFCA and analyze the heat propagation during cardiac ablation when the esophageal wall is cooled down. The esophagus, the connective tissue, and the heart wall were simulated, assuming laminar blood flow in the heart wall. The simulated electrode temperatures were 60, 70, and 80 °C for 60 seconds with constant peak voltage. The cooling temperature was 0 °C. The results showed that cooling decreases the temperature between tissues. The temperature in connective-cardiac tissue dropped by approximately 6.51%. In the esophageal-connective tissue, the temperature decreased by about 28.22%. In all cases, there was also a slowing in temperature increase, which can help prevent tissue damage. The results suggest that the method has significant potential for improving the safety of RFCA.

Laboratory tests conventionally used to determine blood typing could represent a barrier to patients with reduced accessibility in emergency situations. Aiming to expand access to a simple and quick laboratory test to identify the ABO and Rh systems, we propose the development of a colorimetric test in a Vertical Flow format. The test was developed based on the treatment of chromatographic paper membranes, in order to filter the red blood cells after the reaction with the antibodies impregnated inside the device. When the blood reacts with the membranes, the plasma passes through the device forming a visible bluish complex on the last membrane. The prototype showed satisfactory results when tested on real samples, visibly showing the presence or absence of reaction in the samples added to the device, enabling the determination of the ABO and Rh systems with accuracy.

Cancer is the most frequent cause of death in dogs. Osteosarcoma is a bone cancer common in dogs. Traditional treatments of osteosarcoma involve surgery and chemotherapy. Electrochemotherapy emerges as a possibility to treat the safety margin after a debulking, especially near vital organs like the brain. The use of electrochemotherapy near sensitive tissues to electric stimulation can be an issue. Preserving social aspects (recognition and temperament) is essential when treating a pet. Noxious brain stimulation is related to high electric current density (25 mA/cm2) and high electric charge density (5.24 C/cm2). This paper brings a series of in silico studies to evaluate the electric current density in a dog’s head osteosarcoma treatment in different bone destruction levels, with both needle and plate electrodes. The results show that all simulated cases induce electric currents in the brain. The worst-case scenario occurs when the plate electrode is directly in touch with soft tissues (all bone layers compromised by tumor infiltration), where the maximum electric current density was 3376 mA/cm2. During our discussion, we adjust the transcranial direct current stimulation threshold to the electrochemotherapy exposure time, getting an electrochemotherapy threshold of 6.55 kA/cm2. Even in the worst-case scenario, the calculated maximum electric current density is lower than the safety limit. We considered the application of electrochemotherapy safe near the brain, even with direct contact of the electrodes.

Aim of this work was to conduct a pilot study on the use of thermography to evaluate engorged breasts. Ten lactating volunteers, five normal and five engorged, were evaluated by clinical examination and thermographic images. Two regions of interest for breast are selected in the thermographic images. The average temperature in these regions were statistically compared, significance level of 95%. The average normal breast temperature was 34.13 ± 0.71 °C and the abnormal breast 35.03 ± 0.50 °C. These temperatures showed statistical difference when compared between (p-value < 0.05). The data obtained made it possible to analyze the thermographic changes of the puerperal breast, thus contributing to more accurate diagnoses. The results indicated that with clinical examination and infrared thermography, it was possible to delineate a differential pattern between the various events that affect the breast in the lactation process.

Brosimum gaudichaudii (BG) is a medicinal plant native from Brazil and popularly known as mamica-de-cadela, mamacadela, among others. It presents as main metabolites coumarins and furanocoumarins, recognized photoactive agents. There are several studies that indicate the photodynamic action of Brosimum gaudichaudii extracts. The purpose of this study was to perform photophysical studies of the aerial parts of the plant extract for application in photodynamic therapy. The results of this study were determined by the absorption spectrum in the ultraviolet (UV) and visible regions, as well as the emission spectrum when excited at different wavelengths. In the region of 345 nm, the stem extracts stand out, since this region is where bergaptenes and other furanocoumarins absorb light. In the region 667 nm all the extracts were found, mainly those of the leaves, and in this region chlorophyll absorbs light, which shows the contribution of chlorophyll in the process. The photodynamic potential action of the extracts by solar irradiation was attributed to a synergism by action on UV and chlorophyll and its derivatives in the photodynamic therapy.

In electrochemotherapy, needle electrodes can be used to apply electric fields in biological tissues to catalyze chemotherapy drug effect. Electrode bending, which is not entirely unavoidable, may affect the capacity of covering the entire tumor mass by insufficiently high electric fields. This paper aims to study how electrode needles misplacement affect the effectiveness of EQT, using in silico and in vitro experiments to analyze inwards and outwards bending. We observed an electric current increase at inwards bending. On the other hand, the electric field distribution is disturbed when they bent outwards. Both cases may induce treatment effectiveness loss. Based on those results, it is recommended to avoid usage of electrodes with mechanical deformations during electrochemotherapy treatments.

Electrochemotherapy (ECT) is a cancer treatment that combines chemotherapy and electroporation (EP) where EP is used to increase cells membrane permeability, facilitating the entrance of drugs into cancer cells. For successful treatment, the entire tumor region needs to be exposed to an adequate electric field intensity. In silico and in vitro studies are used in a pre-treatment step to analyse the electric field distribution and possible mistakes, especially in irregular and complex tissue structures such as protuberances and holes. Conductive gels can be used to fill irregular tissue structures and make the electric field distribution homogenous. In this paper, an in silico study and in vitro vegetal model were used to evaluate the effectiveness of commercial conductive gels in electric field homogenization of discontinuity areas. Both studies demonstrate that conductive gels were effective in homogenizing electric field in the discontinuity region.

Commonly used to the diagnosis and monitoring of different diseases, such as Addison’s and Parkinson’s, or stress association, cortisol is a steroid glucocorticoid that has a special interest for the medical community. The present work approaches the study of the cortisol infrared spectrum in order to reveal vibrational markers for the quantitative determinations of salivary cortisol levels. For this, the infrared spectrum of the cortisol molecule was obtained by computational methods, based on the Density Functional Theory (DFT), using Avogadro, Gaussian and VEDA software. The stretching of the double C–O bonds highlights as a more intense region of the infrared spectrum of the cortisol molecule. A set of assignments for the majority vibrations has been suggested. The experimental spectra of the analytical standard of cortisol, artificial saliva and artificial saliva with cortisol addition were obtained in the reflectance mode using an ATR accessory. The theoretical spectral profile was compared to the experimental values of the vibratory modes. Finally, the vibrational bands at 2912, 1714, 1706, 1642, 1630 and 1610 cm−1 were highlighted as potential vibrational markers for the determination of salivary cortisol concentration, pointing out that infrared spectroscopy can be used for qualitative and quantitative analysis of salivary cortisol levels.

The aim of this research was to detect spectral differences in glycemic components. Urine samples were collected from 40 patients who were divided into a control group and a diabetic and hypertensive group. The samples were obtained in the morning, fasting, and stored a freezer at − 80 °C until spectral analysis. Spectral data collection was performed using a dispersive Raman spectrometer (Dimension P-1 model, Lambda Solutions, Inc., MA, USA). The equipment uses a stabilized multimode diode laser operating at 830 nm, with about 300 mW power output, and time integration to collect the Raman signal was adjusted to 5 s. The mean Raman spectra displaced from the urine of patients in the study groups (CT and DM & HBP) were identified at the range of 516 and 1127 cm−1. Comparative analysis of mean urine spectra showed a significant difference (p < 0.05) between the groups, the Student's t-test was used to compare the mean Raman spectra of the groups. The comparative analysis of peak intensities at 516 and 1127 cm−1 in the urine of diabetic control and hypertensive patients revealed that it was higher in the DM & HBP group than in the CT group, however, with no significant difference (p > 0.05). To quantify the glucose in urine and discriminate the groups, a model was developed to estimate the concentration using a quantitative regression model based on partial least squares (PLS). According to the data obtained, there was an excellent correlation (r = 0.98) between the concentrations estimated by the model and the concentrations determined by colorimetric analysis. Discriminant analysis (DA) based on a regression model (PLS) proved to be promising as it discriminated the control group without errors, and the rate in the DM & HBP group was 89.1%. Raman spectroscopy can be a potentially useful tool for testing glucose in urine.

Therapeutic Hypothermia is a technique that involves an intentional and controlled, systemic or selective body cooling, for the treatment of conditions such as traumatic brain injury, stroke, and after cardiopulmonary resuscitation. Decreasing body temperature to below normal levels is a proven clinical intervention and has been used in operating rooms since the 1950s and in the early twenty-first century gained recognition as a neuroprotective agent. There are currently several cooling techniques available which can be invasive or non-invasive, each one has its advantages and disadvantages. The ideal method would be one capable of rapidly inducing hypothermia without risk of overcooling, maintaining the target temperature during the maintenance phase, with minimal oscillation, providing controlled and slow rewarming and being minimally invasive. Each case should be evaluated individually to define the best cooling method to be used. This paper presents a new low cost, safe and easy operation equipment of induction and maintenance of moderate Therapeutic Hypothermia. The system involves direct cooling of the blood through cardiopulmonary bypass, using the same blood lines from hemodialysis procedures, which are fitted in heat exchangers, so that blood cooling occurs within the circuit itself and no contact with any other equipment. The central function of this equipment is to decrease the patient's systemic temperature in order to reach the pre-set target temperature of hypothermia as rapid as possible (induction phase), control the hypothermic temperature precisely to maintain minimal fluctuation (maintenance phase) and slow and controlled rewarming of the patient until the normothermia (rewarming phase).

High-intensity lasers are widely used in dental procedures and the heating produced on the surface is necessary to ensure protective activity against the development of caries and erosion lesions. However, caution should be exercised regarding the spread of heat to the pulp, periodontal tissue and alveolar bone, which can cause harm to these tissues. This study sought to evaluate the generation and transmission of heat in the root dentin and adjacent tissues during irradiation with Nd:YAG laser for preventive activity. For that, 15 lower incisor human teeth had an area of 9 mm2 of root dentin irradiated with Nd:YAG laser (λ = 1.064 µm, 10 Hz, 60 mJ/pulse, 84.9 J/cm2) for 30 s. During irradiations, pulpal temperature was evaluated by fast-response thermocouples, while surface temperature and heat distribution on surrounding tissues were measured by infrared thermography. It was observed a mean surface temperature increase of 293.48 ± 30.6 °C in root dentin surface, and 15.85 ± 39.6 °C below the irradiated area, 11.72 ± 8.7 °C above the irradiated area, 19.77 ± 4.9 °C at 1 cm laterally and 7.03 ± 2.7 °C at 2 cm laterally to the irradiated area. The mean pulpal temperature augment registered was 6.5 ± 1.4 °C. It can be concluded that Nd:YAG laser irradiation promoted surface temperature rises that suggest chemical changes on dentin; however, the temperature increases generated in the adjacent tissues (region of periodontal ligament) and in the pulp chamber may be dangerous in future clinical application considering the irradiation time of 30 s made in this study. Therefore, this laser protocol can be used as long as the irradiation time is reduced in future studies.

Methylene blue (MB) is used for Photodynamic Therapy (PDT), with a protocol which is efficient, inexpensive, and safely, used for decades in clinical applications. The quantification of efficacy of a photosensitizer in aqueous solution is well known in literature. Photobleaching, a photoinduced degradation or modification of photosensitizer, can procedures significant lack of efficacy in PDT treatment since the generation of reactive oxygen species is directly associated with photons absorption of this photosensitizer. In this paper was studied the Photobleaching kinetics of methylene blue in presence of hydrolyzed collagen. In the investigated conditions, where the collagen matrix simulates the cytoskeleton net, it was demonstrated that the compartmentalization of MB can modulate its photobehavior, how bigger MB concentration in collagen medium, smaller Photobleaching rates. We associated this behavior to methylene blue concentration and by the environmental interaction.

The colonisation of the pilosebaceous follicle by Propionibacterium acnes (P. acnes) is known as one of the main factors driving acne by taking part in the inflammatory response of the skin. Antimicrobial Photodynamic Therapy (aPDT) has important applicability in skin diseases, however its use with hypericin (Hypericum perforatum) photosensitizer for inhibit of P. acnes have not yet been clarified. The aim of this study was to evaluate in vitro the effects of aPDT using hypericin photosensitizer associated with red low-level laser therapy on P. acnes biofilms. The biofilms were placed in 96-well microplates by using standard suspensions (2 × 107 CFU/mL) and grown in BHI broth for 48 h in anaerobic chamber. Subsequently, the control group received application of 0.9% sterile saline solution for 3 min (C); laser groups received irradiation of energies of 3 J (L3J); hypericin group at concentrations of 15 μg/ml for 3 min (H15%); aPDT group received 15 μg/ml concentration of hypericin associated with laser energy of 3 J (H15%L3J). After the biofilms were broken up and seeded for CFU counting. The results showed a reduction in P. acnes biofilms in H15% and H15%L3J. In addition, this reduction was higher in H15%L3J. This study showed that hypericin and aPDT using hypericin photosensitizer showed effective antimicrobial action for inhibiting P. acnes biofilms and may be promising resources in the clinical treatment of acne vulgaris.

Objectives: This study was carried out to evaluate the analgesic effect and the thermal distribution of the treatment through acupuncture in patients with chronic pain and vascular disorders in the lower limbs. Methods: Two female patients undergoing clinical follow-up at the Hospital de Santo António, Portugal. The skin temperature of the lower extremity regions was measured before and after the acupuncture treatment at acupoints B17, BP10, BP6 and IG4, by infrared medical thermography. Thermographic data were analyzed by ThermaCAM Researcher Research Pro® 2.10 software, establishing the average temperature in the regions of painful symptoms. Results: When painful symptoms fadeout, the average temperature in the regions of interest has decreased 0.5 ℃ in the Anterior Tibial Muscle, 1.3 ℃ in the Gastrocnemius Muscle, 1.0 ℃ in the Soleus Muscle, in patient 1; and 0.6 ℃ in the anterior Tibial Muscle, in patient 2. Conclusions: Despite the small sample size, it indicates that infrared thermography may be applicable in the area of acupuncture, presenting sensitivity in diagnostic and monitoring the treatment of chronic pain related to vascular disorders in the lower limbs.

Paracoccidioidomycosis (PCM) is a disease caused by the fungus Paracoccidioides brasiliensis (Pb), manifesting as a systemic mycosis, which can lead to death. This study evaluated the action of in vitro Photodynamic Inativation (PDI) on Pb yeast cells through the LED light source (LEC Prime WL—MMOptics: 455 nm, 0.8 W/cm2 and 0.2 W with 6 mm tip) associated with the photosensitizer (Fs) curcumin 98%. The photodynamic action was performed with 4 groups and 6 application cycles of the technique, fractionated every 5 min, for a total cycle of 30 min. The tests were performed in quintuplicate and the groups were divided into: group 1—without Fs in its composition and without LED irradiation (L−F−); group 2—without Fs and with exposure to irradiation (L+F−); group 3—with Fs and without exposure to LED irradiation (L−F+); and group 4—composed with Fs and exposed to LED irradiation (L+F+). The results showed that the reduction of Pb, measured by the means of CFU Log, was significantly higher in group 4 (0.7748 ± 0.1876) when related to group 1 (2.399 ± 0.09470) (p < 0.001), group 2 (2.178 ± 0.08214) (p < 0.001) and group 3 (1.818 ± 0.09987) (p < 0.001). There was elimination of the fungus P. brasiliensis from the 20th minute of irradiation in the group exposed to the LED associated to the presence of Fs (p < 0.001). We concluded that PDI associated with the administration of curcumin 98% is capable of promoting the in vitro elimination of the pathogenic fungus Paracoccidioides brasiliensis.

Cleaning and disinfecting surfaces and materials in health services are primary elements in infection control measures. For thermosensitive materials, the chemical agents used have disadvantages such as the odor of the products, which can cause allergic reactions to patients and the nursing staff. Photodynamic therapy (PDT) has been shown to be an effective technique in the treatment of infections caused by different microorganisms; however, nothing is known about the effects of this technique on the microstructure of hospital supplies. This in vitro study aimed to evaluate the effects of 0.2% peracetic acid, 1% sodium hypochlorite and PDT with 0.01% methylene blue on the composition and color changes of hospital masks and extensions. For this purpose, 100 mask samples and 100 extension samples were randomly distributed in 20 experimental groups (n = 10, 10 groups for each material), in which the applied substance was varied (sodium hypochlorite, peracetic acid and PDT) and the number of applications (without application, 1, 2 or 3 applications). The compositional analysis was performed by Fourier transform infrared spectroscopy, while the color changes were evaluated using image analysis by CIElab method evaluating the parameters L*, a*, b* and ΔE. The statistical analysis was performed at 5% significance level. It was observed that all agents altered the composition of the materials in a similar way. Although all agents promoted changes in different parameters evaluated, peracetic acid and methylene blue alone altered the final color perceived only in extensions. It was concluded that 0.2% peracetic acid, 1% sodium hypochlorite and PDT alter the chemical composition of both masks and extensions, and that such changes have a positive relationship with the number of treatments performed. These compositional changes may be related to the color changes promoted in both materials by all agents tested.

The present work describes the technological development of a low-cost and miniaturized instrument to Polymerase Chain Reaction (PCR) for detection of Sars-CoV-2 ribonucleic acid (RNA) and, potentially, an open platform for detection of other microorganisms. Most devices use a big aluminum bar coupled to a peltier to heat and cool the reaction tube; however, a lot of energy is wasted in the process. To take advantage of the energy and reduce cost–benefit of the device, we introduced the Joule Effect in the printed circuit board for heating samples, and a computer fan for cooling. Other improvements such as a precise heating sample spot, and a LM35 thermal sensor with a PID (proportional integral-derivative) algorithm to control the circuit temperature, have also been included. The processes were carried out based on cost–benefit and performance to bring to the market a robust detection platform for in vitro diagnostic tests.

The root caries lesions still represent a health problem due to their rapid progression and, therefore, more efficient remineralization strategies are necessary. High-intensity lasers are useful because they modify the microstructure of the irradiated tissue due to heating; however, nothing is known about the effects of these lasers when associated with bioactive materials to remineralize caries lesions. This study evaluated the compositional changes that the Q-switched lasers emitted in the spectral region of infrared (IR, 1064 nm) and ultraviolet (UV, 355 nm) make in Biosilicate® on dentin with incipient caries lesion. Sixty blocks of demineralized root dentin were randomly divided into 6 experimental groups, to be treated with Biosilicate® alone (10% in fetal bovine serum), lasers alone (IR or UV, 5 ns, 10 Hz, 5 pulses/sample, 250 mJ/pulse or 100 mJ/pulse, respectively) or laser irradiations after 24 h of Biosilicate® application. After 24 h immersed in artificial saliva, samples were evaluated by Fourier transform infrared spectroscopy between 450 and 4000 cm−1. Laser irradiation alone reduced the organic, carbonate and water contents of the dentin, with greater effects promoted by the IR-laser as a result of heating. Biosilicate® alone elevated the content of phosphate and carbonate, which suggests formation of carbonated hydroxyapatite (HAC) on dentin. The irradiation with UV-laser after Biosilicate® also promoted an increase in the phosphate content, however there was less conversion of the biomaterial, evidenced by the rise in the intensity of the bands corresponding to the siloxane and amorphous phase of the apatite. Irradiation with IR-laser after Biosilicate®, on the other hand, promoted a significant increase in phosphate content when compared to the group treated with Biosilicate® alone, without the presence of siloxane bands. It was concluded that laser irradiation can augment the bioactivity of the Biosilicate®, evidenced by the greater formation of HAC and, for this, the wavelength of 1064 nm should be used.

Plants are organisms that produce and store diversity of bioactive substances, between primary and secondary metabolites. Secondaries can have therapeutic properties and are called active ingredients. Salpichlaena volubilis, in Amazonas is known as “Rabo de onça”, the parts used as remedies are the leaves and rhizomes. In the scientific literature, no records were found about this species in the treatment of diseases, only reports of use for the treatment of alopecia areata. To evaluate the first technical-scientific essay, two methods were used: the first method used was to capture the organic radical DPPH·, the second was to characterize 1O2.The work aimed to evaluate the antioxidant activity of the ethanol extract of S. volubilis and its correlation with alopecia areata. To compare the determination of antioxidant action, the standard model of capture of organic radicals DPPH·/TROLOX and the extracts of S. volubilis were used. The results are presented in the UV/visible absorption spectra and in the kinetics of the extracts, being significant compared with the standard model.The leaf/rhizome extract showed the best suppression of DPPH·, 80% in five minutes. In the characterization of the 1O2 evaluated with emission at 532 nm when excited at different wavelengths, it was possible to observe that the extracts, compared with the blue methylene/acetonitrile model, present singlet oxygen generation. In the emission spectrum of 1O2 irradiated at 532 nm, the leaf extract/ACN showed a spectral curve characteristic to the generation of 102 with maximum absorption at 1270 nm. While the extracts of the rhizome and leaf/rhizome, had little emission of 1O2.

The Autonomic Nervous System (ANS) is responsible for regulating various physiological processes in the human body. The Heart Rate Variability (HRV) represents a measurement used in evaluating the modulation of the ANS in different physiological conditions such as stress, physical activity, sleep, metabolic alterations, and, also, pathological conditions. Physical activity results in important changes in the cardiovascular system, such as an increase in blood flow and a decrease of the peripheral vascular resistance. Monitoring the peripheral microcirculation represents an important aid in evaluating the general conditions of an individual. The Laser Speckle Contrast Analysis (LASCA) is a non-invasive optical resource developed that uses nonionizing radiation in the region of the infrared and is important in the diagnosis of problems regarding the peripheral microcirculation. This work aimed to implement a method to obtain the HRV through the peripheral microcirculation utilizing the Laser Speckle Contrast Analysis (LASCA) technique. A commercial LASCA equipment was used to obtain a face-video. A custom software was implemented to process the LASCA videos and obtain the HRV. A heart rate monitor (HRM) was also utilized to measure the HRV and the values were compared against the ones obtained with LASCA. The method had consistent results in obtaining both the pulsation and the HRV, making it possible for future studies to use such a technique.

Osteoarthritis is a degenerative joint disease that commonly affects weight-bearing joints, being the knee the most affected one. Treatment options include invasive therapies and non-pharmacological therapies (pain education, exercise programs, electrotherapy, acupuncture and ozone therapy). Another form of treatment that has been increasingly studied and used in patients with knee osteoarthrosis is photobiomodulation therapy, which despite its conflicting results has been considered effective in reducing the inflammatory process when used alone or associated with exercise programs or acupuncture. When associated with acupuncture, laser has proven to be effective despite few high-quality randomized controlled studies on the subject. Recently, patients have been seeking less and less invasive and natural treatments, making more and more professionals train, practice and research the effects of treatments such as acupuncture and laserpuncture. Objectives: To conduct a literature review on photobiomodulation for the treatment of KOA, focusing on the use of low-level laser therapy associated with acupuncture points. Methodology: An integrative literature review was carried out between March and May 2020 on PubMed and the Physiotherapy Evidence Database (PEDro). The selection criteria used were English language and articles published in the last 10 years that included the keywords: “knee”, “osteoarthritis”, “photobiomodulation”, “laserpuncture” and “acupuncture”. Results: Out of the 50 articles found, 30 were selected for presenting methodology or applications of replicable techniques. Conclusion: After this review, we could note that there is still a very small number of controlled and randomized articles with relevant data on the effects of photo-biomodulation in acupuncture points for the treatment of KOA. Additionally, we could observe that the surveyed articles differ in their forms of tabulation and data analysis, making it difficult to compare them. We suggest that further studies be performed on the subject to produce more relevant data and make the use of these therapies a consensus.

The intraocular-lens (IOL) industry revolves mainly on manufacturing different types of lenses to restore the vision quality of patients through ophthalmic surgery. This paper introduces a biconvex intraocular lens with a bidimensional refractive sinusoidal profile distributed over its posterior surface. This type of pattern allows the configuration of different amplitudes and frequencies of the orthogonal sinusoidal functions, leading to different optical performance. By adjusting its parameters, it is possible to set the IOL to behave as Monofocal, Multifocal or Extended Depth of Focus. Therefore, a methodology that could assist in the classification of such lenses is proposed. The intraocular lens under test is modelled and inserted into a modified Liou-Brennan eye model. This methodology can be used as a trusted tool to help lens manufacturers in industry to determine optimal target design parameters.

Raman spectroscopy is a high-resolution photonic technique that can provide, in a few seconds, chemical and structural information on almost any material, organic or inorganic compound, thus allowing its identification. This technique has been used in the food industry to detect adulteration in food products and to characterize new chemical compounds. In this work, we used the Raman technique to elucidate the composition of cassava flour that provides 3.92% of the daily energy for Brazilians. Different samples of flour produced industrially and artisanal (in the flour houses in the interior of the country and sold at open markets) were analyzed. The objective of this work was to discriminate by origin and determine which vibrational modes characterize these samples of artisanal and industrial cassava flour by Raman spectroscopy technique. From artisanal and industrialized cassava flours spectra analysis, it was found that the principal Raman peaks are located between the 300 and 3000 cm−1 bands. This fact leads us to suggest that cassava flour has in its composition complex carbohydrates such as polysaccharides, unsaturated fatty acids and proteins, characteristics founds in plant origin’s food. With the present work we were able to carry out for the first time a artisanal and industrialized cassava flours chemical analysis by the Raman method.

Radiotherapy can cause radiodermatitis in 85–90% in oncologic patients. There are several therapeutic alternatives to treat radiodermatitis with variable results. A new option is the use of light emitted-diode (LED) to treat this condition. We analyzed twenty male Wistar rats weighing 200–250 g. All the animals underwent a radiotherapy session. After 15 days, the animals were divided into four groups: control (no treatment) and LED 630 nm, 850 nm, 630 + 850 nm. The LED treatment was applied every two days until the 21 days). We analyzed the macroscopic aspect of radiodermatitis before and after treatment. After this phase, samples were collected for histological (HE). Macro and microscopic analysis indicated positive effects with exposure to light, especially with the association between wavelengths 630 and 850 nm, resulting in a reduction in the severity of radiodermatitis to grade 2–2.5. In the histological analysis, photobiomodulation increased the division and migration of cells in the basal layer of the epidermis, demonstrating the regenerative potential of this treatment in the effects of radiotherapy, increasing the speed of epithelialization of the lesion. This study suggested that the association of 630 + 850 nm improved radiodermatitis regeneration.

Biomaterials are employed to aid bone regeneration in localized bone defects, especially when there is a great loss of tissues, compromising their ability to repair. A new generation of lithium disilicate glass-ceramic presents favorable characteristics for bone reconstruction, such as high strength and bioactivity. In turn, photobiomodulation therapy has been studied in order to stimulate bone metabolism since it acts as a modulating agent for tissue regeneration. In this study, we evaluated the effect of photobiomodulation therapy on the interaction between osteoblastic cells and lithium disilicate glass-ceramic. MG63 cells suspension was seeded on lithium disilicate and glass discs. After 24 h samples were irradiated with a LED device ( = 660 nm) with 50 mW/cm2, 2 J/cm2 for 40 s. Cell viability was assessed 2, 7, and 12 days after irradiation using MTS assay. Samples previously stained with alizarin red S were observed at a confocal microscope to evaluate calcification of bone matrix. We first observed an increase in the number of cells adhered to lithium disilicate, compared to glass discs on day 2. LED irradiation promoted an increase in the number of cells on day 12 in both irradiated groups, being quantitatively higher on disilicate discs. Disilicate discs also showed a higher deposition of calcium on the extracellular matrix compared to glass. Red light anticipated mineral deposition for all irradiated groups, being earlier for disilicate samples. In conclusion, photobiomodulation therapy anticipated the positive effects of lithium disilicate glass-ceramic on bone matrix formation and mineralization.

Semmes-Weinstein monofilaments have been widely used to quantify touch sense thresholds. However, it is an instrument of low sensitivity with subjective responses. In the 1980s, a procedure was proposed for the psychophysical assessment of touch sense by sine-wave electric current stimulation. This assessment was based on studies that suggested sinusoidal stimuli of different frequencies would excite sensory systems related to fibers of different diameters, thus increasing the selectivity of the stimulation. This study aims to evaluate and describe the CPT Reference values for the upper limbs nerves of healthy Brazilian subjects using sine-wave electric stimulation. Sixty-five healthy subjects were included, which 36 were male and 29 were female. The mean of age was 45 years (±20).All subjects had the ulnar, median and radial nerves evaluated with a sine-wave electric stimulator (NEUROSTIM) to quantify the Current Perception Threshold (CPT), for the frequencies 1, 250 and 3000 Hz. No statistical differences were found when comparing different limbs on the same patient, neither when comparing genders. There was only significant difference in between groups of different ages for the 1 Hz frequency on the Ulnar nerve, and for the 250 Hz on the Median nerve (p < 0.05). The NEUROSTIM evaluation protocol seems to be effective, objective and able to be replicated for sensory loss evaluation. Having reference values in the CPT of Brazilian adults can help professionals in the clinics to have a better understanding, management and treatment of diseases that affects touch sense, such as leprosy, diabetes and others.

The Ophthalmic Instrumentation Laboratory (LIO) from the University of Sao Paulo—Brazil, was involved in research about sunglasses and its standards, and has already contributed for changing parameters in the previous Brazilian sunglasses standard. According to the standard used in Brazil, depending on luminous spectral transmittance, lenses are classified into different categories and for each category there is a required UV protection. In this work, we evaluated the UV protection of a representative sample of the sunglasses available in the Brazilian market. Most of the 231 samples were from unbranded sunglasses, and all of the samples had the same conditions as if they were sold to costumers in the informal market. In our analysis, all the branded samples were approved in the UV protection test, and by buying lighter color sunglasses (categories 1 and 2), the costumer might be more subjected to find a unbranded sunglasses that don’t have UV protection.

In recent years there has been growing interest among the public and scientists in blue-light protection. We analyzed blue-light protection in sunglasses available on Brazilian market, separating them according to their categories. We measured lens transmittance using a VARIAN Cary 5000 spectrophotometer, and we calculated luminous and blue-light transmittance. A sunglasses lens is considered to be minimally safe against blue light if its blue-light transmittance is less than 1.2 times its luminous transmittance. From 222 unbranded lenses, 4.5% of them fail our test of blue-light protection and 2.7% of them are excessively dark. This study is part of a series that intend to investigate optical characteristics of sunglasses on Brazilian market in order to evaluate whether they provide enough safety and protection against harmful solar radiation to the public. We believe that our analyzes may improve knowledge about the quality of sunglasses available on Brazilian market.

Diabetic foot is one of the most common complication of Diabetes Mellitus (DM) that arises along the evolution of this disease. Diabetic neuropathy tends to be a progressive pathology, affecting more aggressively patients with poor glycemic control. Generally, the clinical examination includes detailed feet evaluation to determine areas of diminished sensitivity, using Semmes-Weinstein Monofilaments. Infrared thermography is a modern high-resolution technique that may measure thermal alterations referring to vasomotor changes, which may indicate neuropathies. So, the aim of this research was to correlate thermal changes in the feet with tactile sensitivity alterations in type 2 diabetic patients at risk for diabetic peripheral neuropathy. It is a cross-sectional qualiquantitative study, achieved with 10 participants. The two assessment techniques used favor early diagnosis for people with type 2 DM and a better clinical course of the disease, reducing the high costs for public health and improving the quality of life of people with DM.

The main goal of this research was to develop a custom made 3D printed thumb orthosis model prototype, able to reduce the necessary effort during part assembly in an automotive industry. Several materials and models were designed, 3D printed and evaluated using surface electromiography. Results show a significant reduction of the evaluated sEMG parameters when using the proposed orthosis that can lead to a decrease in occupational risk.

This paper presents an analysis on recently (2017–2019) developed myoelectric hand orthosis for Spinal Cord Injury (SCI) and Stroke patients. The analysis was based on concepts of Interaction Design, User Experience (Donald Norman), and Usability (Jakob Nielsen) to show how the lack of User-Centered design leads to poor outcomes. It was identified that ignoring these factors compromises entire developing processes, requiring re-design, as pointed out by most studies. A structure was constructed to survey selected parameters, and we propose its use to serve as de facto guidelines to develop such technologies, emphasizing on a User-Centered approach. It was also identified that no device had Brachial Plexus Injury as object of study and current socioeconomic scenario in Brazil suggests that these individuals might go through hardships without any device to support them, hence, this article raises awareness about this particular condition.

Population aging and the increasing costs of health care, especially for the elderly affected by chronic diseases, requires new medical assistance strategies that makes it possible to monitor these people remotely and provide reliable information on their routines. In this context, human activity recognition (HAR) systems are an important element to overcoming the problem. Therefore, this paper proposes a HAR system prototype containing a multilayer perceptron (MLP) as a classifier. The model hyperparameters were selected using a publicly available dataset. Then, data was collected from accelerometers and gyroscopes embedded in wearable devices of 15 subjects while performing six basic activities (walking, sitting, lying down, standing, walking upstairs and walking downstairs). The system reached an average accuracy of 90.74% and weighted F-measure of 90.03% based on leave-one-subject-out cross-validation.

Interaction models are computational representations of human beings interacting with robots and are useful tools in the modeling and simulation of human and robot controls. In this work we used an interaction model between human and an active knee orthosis, with a simulation algorithm in order to model and reproduce a fuzzy-based human control comparing it with a PID-based one. The results proved that this is a possible approach to model the human control used in simulations with interaction models, in addition to prove that computational methods are a flexible and agile tool to develop and model both robot and human controls.

Use of wearable devices (e.g. smart bands) for monitoring of the patients outside hospitals, clinics, and healthcare units can create productive scenarios with excellent cost-benefit. We can imagine reducing unnecessary costs such as those of professionals and physical spaces, for cases that are not required such resources. Another important aspect is that they allow integral monitoring of patients aiming at possible early diagnoses of diseases with high mortality rates, such as cardiovascular diseases. On the other hand, the approach to the Internet of Things (IoT) computing environments represents a set of interesting technologies that can support the aggregation of smart bands differentially. An example is a support for efforts aimed at the health status of the general population. In this dimension, this research presents a survey and a proposal oriented to the use of wearable devices in health care. Firstly, a set of works and prototypes already developed is presented. On the other hand, the main trends and challenges in the use of IoT devices for healthcare are pointed out. Based on the research developed, a low-cost and scalable computational environment is proposed. This environment is based on the IoT paradigm, encompassing the construction of a hardware prototype for health data collection and the development of two software components: a web system and a mobile application, which were developed for the processing and monitoring of the collected data. These data to be stored in computing resources of fog and cloud services with data analysis capability.

Assistive Robotics has been shown to be an important tool in the patient rehabilitation process. One of the first steps in this process is to capture the movements performed by the patient to analyze the movement restrictions presented. The present work presents a brief review of the state of the art as well as the development of a Range of Motion (ROM) measurement system based on the position of the joints in the three-dimensional space of the upper limbs using the Kinect sensor. In addition, preliminary tests to capture compensatory movements of the trunk are presented aiming to investigate the feasibility of using such system as a tool for detecting compensatory movements. Therefore, a methodology is proposed that uses the Kinect sensor to capture the range of motion and compensatory movements in order to assist in the physiotherapeutic process. The results obtained showed the feasibility of using the proposed system for the detection and capture of both the range of motion and the compensatory movement of the trunk.

N-MARIA (New-Mobile Robot for Interaction with Autistics) is a robot developed at the Federal University of Espirito Santo (UFES/Brazil) to assist and interact with autistic children. This Child-Robot Interaction (CRI) is conveyed through different controllers, such as orientation and position controller, leader-follower formation controller, Repetitive Controller (RC), and RC plus Proportional-Integral (PI) controller. This work presents firstly the use of a repetitive controller, and then uses the RC plus the PI controller to implement a “play” mode to be played during a CRI. In this mode, a periodic setpoint is used to allow the robot to approach and move away from the child. Using the RC for this mode, the robot is able to follow the generated trajectory with small error, even with periodic setpoints. When using RC plus PI, the experiments show smaller tracking error.

The use of hands during communication is generally a natural way of communication and allows the transmission of messages. However, in order to communicate with deaf people using sign language, it is necessary to know the rules of sign language. In this way, tools and technologies for communication between deaf people and listeners are very important to improve the social inclusion of the deaf community. The wearable hand devices have been used to identify sign language gestures. In this regard, the purpose of this paper is to analyze the contribution of these sensors, individually and in groups, in the classification of characters of Brazilian sign language alphabet. The wearable hand device used is composed of five flex sensors, two contact sensors, and a three-axis inertial sensor (accelerometer and gyroscope). For the dataset, five volunteers executed 26 alphabet characters. For the classification, each gesture window was divided into three parts: construction period, gesture period and gesture relaxation period. Thus, 28 gesture patterns were considered for classification. The used classifier was the Multilayer Perceptron Neural Network (MLP-NN). In the individual sensor analysis, the flex-sensors obtained the highest accuracy rate (79.0%), followed by the accelerometer (41.7%), the gyroscope (32.1%), the contact sensor 2 (7.1%), and the contact sensor 1 (6.9%). In the analysis of the sensors in groups, the set of all sensors was the one that obtained the highest accuracy rate (96.1%).

The leakage of flammable products and toxic gases can cause serious disasters, a scenario that professional rescuers are forced to dealing with. Therefore, it is extremely important to continuously monitor the safety of the environment and the physical integrity of the professional during a rescue. This work aims to develop a wearable smart system for monitoring and analyzing gases in the environment and, at the same time, rescuer’s vital signs. Thus, a hardware-software system based on gas sensors and a heart rate sensor embedded in a commercial smartwatch was developed. An external agent can monitor the data/signals of the rescuer through on IP Access (Web Monitor) and a Mobile Application (App Monitor). Taking into account the dangerous nature of the task, warning signs for the rescuer are based on vibration (embedded also on the smartwatch), lights (ring of LEDs), and a screen OLED (smartwatch). Tests were conducted with the gas sensors and a comparison between Photoplethysmography (PPG) devices for vital signals monitoring. This study demonstrates a methodology of build of a smart clothing to protecting life and preventing accidents with hazardous gases.

The sequencing of the genome of new virus, such as the coronavirus type 2 of the acute severe respiratory syndrome (SARS-CoV-2), is essential and of great importance to mitigate new zoonotic outbreaks, which are caused by mutations present in structural and non-structural proteins that make up the viruses. Sequencing allows tracking the behavior of the virus locally and globally, knowing the route of transmission and spread of the virus, and determine the virulence rate. Current studies have been carried out, using first, second or third generation sequencing techniques, which have allowed reading and analyzing the nucleotides that make up the virus genome. Thus, the benefits of effective technologies to know its genetic composition in the shortest possible time become evident. New technologies are able to monitor an epidemic in real time, monitor the evolution and efficacy of a drug, the development of a vaccine as well as epidemiological advances. This work addresses the Oxford Nanopore sequencing, which is considered the most efficient and applied method for sequencing viruses that cause epidemics. Some of the advantages of using this sequencing are highlighted in this work, such as the ability to perform long readings and be able to obtain sample responses in short time. It’s also able to discover as much information as possible about the pathogen, being an important feature to deal with public health emergencies, such is the case of the COVID-19.

Independence and autonomy represent the capability to make your choices and act the way you want, without needing help. The visually impaired in their daily lives face several difficulties and often need help. To make users more independent, a prototype that uses artificial intelligence and narrates images from a camera attached to the glasses was developed. Some of the functions are facial, object and color recognition, all through machine learning and image recognition. Practical tests were carried out by the authors placing different objects in front of the device to verify if they would be recognized. The results were satisfactory for proof of concept about the device.

The fall of a person can occur at any stage of the individual’s life, but it is more frequent in elderly, representing a high social and economic impact on the country and the world. In this scenario, the prevention and measurement of the risk of falls are considered important markers of quality of life among elderly, because fall is a factor that can negatively impact quality, if occurs. Today, the public health system broadly encourages scientific studies that involve understanding the causes of the fall of the elderly, so that the effective prevention of this episode is achieved, reducing the demand and costs in public health. Thus, in this research, we developed and validated the App FisioBerg a mobile application, based on the Berg balance scale and the Visual Analog Scale (VAS); which assists health professionals in assessing the risk of falls and pain intensity in elderly. This is a technological development study of an application that was created using the App Inventor tool, with usability heuristics for the target audience (physiotherapy professionals and students). Professional physiotherapists (n = 4) and physiotherapy students from the tenth period (n = 10) participated in the usability test. The Questionnaire for User Interaction Satisfaction (QUIS) test was applied after the care of 30 elderly people from the Palmas TO region. The software was widely accepted by professionals and students in the study. The App FisioBerg has information and results sharing, presents the VAS scale, as a differential, besides not presenting advertisements. In conclusion, the application App Fisioberg has the main instruments to identify the risk of falls in the elderly, it is easy to operate, and generates a positive tendency for the adherence of health professionals and students in its use.

The handling and gripping of objects by a prosthesis depend on the precise applied force control and the slip detection of the grasped object. These two features combined allow for the adjustment of the minimum grip force required to prevent slipping. Based on this statement, a system was developed to control the slip of objects, composed of a grip controller, for which the objective was to hold the object, and through the signal of a tactile sensor, slip is detected. An artificial neural network was used to identify the slip event for different types of objects. If the response from the classifier is positive, indicating slip, the system sends a signal to the grip controller, so that it increases the grip force performed on the object, aiming at minimizing slippage. In the end, the performance of the system for different objects was analyzed; the result encountered was that the system efficiency is proportional to the mass and the rigidity of the grasped object.

This work presents an Electrical Stimulator (ES) system able to connect to different external sensors and to perform different stimulation strategies that would meet the current research needs on FES-assisted activities, including cycling and walking. An ES with a 3-channel architecture was first developed and later evolved into an 8 and 12-channel system. Each of these channels can generate different pulse waveforms, biphasic or not, achieving pulse amplitude of 100 mA and pulse width up to 1000 $$\upmu $$ μ s at a maximum frequency 100 Hz. To enable protocols involving different stimulation arrangements for a specific muscle, an electrode multiplexing circuit was developed. Data obtained from the functional activity can be exchanged by a wireless interface with an external platform for later offline processing. Inertial Measurement Units (IMU) can be used to calculate the joint angles of the moving limbs. This paper aims to present a brief description of the hardware and the results obtained as the platform configured as a Foot Drop Stimulator. Gait phases were detected through mechanical and inertial sensors. The identification results were compared with data obtained from a gold-standard Qualisys/AMTI system. The developed system evidences its applicability in contexts such as walking, cycling and can also be used for clinical rehabilitation purposes.

Concerning the growing participation of women in the labor market, there are few studies on the influence of work on pregnancy and the absence from work during pregnancy, which makes difficult to develop public health policies for pregnant workers. This work evaluated the self-reported color/race and the absence from work in 502 puerperal women aged 19 years or older and non-indigenous, at Manoel Novaes Hospital, in Itabuna, Bahia—Brazil, through the application of a form. A Bayesian network was created using Bayesian Search (BS) learning algorithm. In the sample, 6 puerperal women declared themselves yellow (1.20%) and of these 2 (33.33%) absented from work during pregnancy, 49 declared themselves white (9.76%) and of these 24 (48.98%) absented from work, 322 declared themselves brown (64.14%) and of these 130 (40.38%) absented from work and 125 declared themselves black (24.90%) and of these 54 (43.20%) absented from work. In the Bayesian analysis, the largest inferences related to absenteeism was the black-race with 46%, contrasting with data from the frequentist model, where the white-race has the highest rate of absenteeism, similarly the lowest rate was in the mixed-race (mulatto) with 39% and the frequentist method was the yellow one with the lowest rate. The collected data increase the knowledge of the main causes of absence in pregnancy and the importance of the topic and the lack of studies justifies that more studies be carried out. It was possible to create a Bayesian network from data collected from puerperal women using the BS learning algorithm and infer about absenteeism considering the self-declared color/race as the input nodes. The Bayesian analysis of the absence from work during pregnancy is an important tool for the study of the topic and makes it possible to develop software for decision making by health professionals during pregnancy.

Prostheses are devices used to substitute specific members of the human body, whether upper or lower limbs. They have become useful either for the amputee population or for those who have a congenital deficiency. There is not a consensus on how to develop a whole myoelectric prosthesis. The literature is mostly fragmented and it is hard to find a monolithic work about it. Thus, the main goal of this work is to summarize all element and systems of a myoelectric controlled robotic hand and pinpoint the trends and detail major issues and recommendations such as the use of biofeedback, EMG classification trends, compliant mechanisms and the current commercial devices.

Proxemics is a theory of non-verbal communication that explains how people perceive and use space to achieve communication goals. This work shows a proposal to use concepts of proxemics associated with a control law to a socially assistive robot to operate as close as possible of children with Autism Spectrum Disorder (ASD) in therapies. A set of software libraries and tools named Robotic Operating System (ROS) is used to make this project reusable. The analysis of asymptotic stability of the system is presented here, and the control law is tested in simulation. Results show that the proposed control law worked as expected, with the robot interacting with the child along the space, following the concepts of proxemics implemented by a finite state machine.

The recent incorporation of robots in therapies to improve the quality of life of children with some type of physical or intellectual disability demonstrates that robotics has reached an important role in contemporary life. These robots have instruments that aim to stimulate social, cognitive and physical skills in these children, allowing an improvement in their behavioral and/or physical aspects. This work proposes the development of a new socially assistive robot, termed MARIA T-21 (Mobile Autonomous Robot for Interaction with Autistics, with the addition of the word T21, meaning Trisomy 21, which is used to designate children with Down Syndrome (DS)). This new robot is to be used in psychomotor therapies with children with DS (contributing to improve their proprioception, postural balance and gait) as well as in psycosocial therapies with children with Autism Spectrum Disorder (ASD). This robot uses, as a novelty, an embedded mini-video projector able to project serious games on the floor or walls to make funnier already established therapies to chilren with DS and ASD, thus creating a motivating and facilitating effect for both children and therapists.

The present work consists of the integration of a motion tracking device using an inertial sensor to control a motorized wheelchair with neck flexion movements and incorporating the device into a training environment to use the wheelchair in Virtual Reality. Training makes it possible to ensure a better performance when using this technology on a daily basis, avoiding accidents and any type of discomfort. The target audience is people with disabilities that require a motorized wheelchair, but are unable to use the traditional control present in this device (joystick), due to impairment of the upper limbs. The implementation of the software for the control module was made easy for users to operate and simple to integrate with additional devices, if necessary. From initial experiments with healthy people, it was possible to prove the relevance of the proposal and the necessity of future improvements for the project.

The exponential growth of health data in the world is evident. Thus, traditional analysis of variables is not viable due to the large volume. The use of artificial intelligence in the exploratory analysis of mortality data from Brazil through unsupervised machine learning algorithms is proposed. The basis used for the study was a modified DATASUS mortality database, in the interval between 2007 and 2017. After pre-processing, of the 13.040.656 lines and 166 variables from the original base, 3.021.787 lines and 36 variables remained. Using Konohen’s self-organizing map algorithm, component maps of the final variables were extracted. The insights extracted directly from the comparison between the maps were confirmed by a statistical analysis of the data. Therefore, it is notable that the use of such algorithms in the exploratory analysis of data, even in Big Data scenarios, become extremely recommended for the creation of guiding data studies.

Individuals, with mental or physical disabilities, need that others know their localization within an indoor environment in order to receive adequate healthcare. This paper presents an indoor positioning system based on a received signal strength indicator (RSSI) sensor network, where positions are determined by an artificial neural network (ANN) from the received signals. This work investigates the effect of using the past and present data from the other sensors to estimate one missing signal, using a second ANN, and using it as a virtual sensor in the main ANN. For the study, a database was built in a typical residential environment with one transmitter and four receivers. The research studies the effect on the performance caused by the failure of one sensor showing the gains of using virtual signals, as well as a comparison of this virtual data with the measured data. The ANNs are trained with the cross-validation method to avoid overfitting. The selected number of neurons in the inner layer, for each case, was the complexity capable of presenting at least the same performance of an oversized ANN, which was also trained without overfitting. The system developed achieved a considerable efficiency, being able to reproduce the position of the individual with less than 0.36 m of average error when all four receivers were working properly. However, this average error can increase to 0.52–0.91 m when a receiver is at failure, depending on which one fails. Nevertheless, the use of the proposed virtual sensor can diminish about 0.2 m of average error in case of failure. Therefore, the use of virtual data proved to be a feature capable of improving positioning when a sensor fails, in relation to the alternative of performing this positioning without this sensor nor its corresponding virtual signal.

Techniques for Human-Robot-Environment Interaction allow sharing control between assistive devices, such as Smart Walkers, and its users by taking into account dynamic environments composed of objects and people. This work presents a simulation platform to accelerate the development and evaluation of such interaction strategies. To enhance the physiotherapists’ control during lower-limb rehabilitation therapies, we employ a map-based strategy to map and allow the customization of pre-defined paths. Inspired by hospital layouts, a simulation environment was created to test and evaluate our system, and two experiments were conducted. In the first one, an accuracy analysis of generated maps was performed in comparison with the actual hospital environment. In the second experiment, we evaluated the avoidance obstacles strategy by positioning unknown objects along the Smart Walker targets. In the first experiment we obtained percentual errors around 2.658 and 8.356% between the original and mapped segments. In the second experiment, besides reached all the targets without collisions the position errors were between 0.062 and 0.118 m and the orientation errors, 0.024 and 0.044 radians. These results indicating the feasibility of employing such methodology for the development of the proposed interaction strategy.

Visual impairment can be congenital, or acquired, and is classified as low vision or blindness. In both cases, the person passes through daily difficulties, such as the ability to recognize objects and people, which implies insecurity and mobility problems. Several assistive technologies have been developed over the years (walking sticks, guided dogs, and electronic devices that assist in mobility) aiming to contribute to the integration of the visually impaired into society and guarantee more independence. This work proposes a wearable echolocation system for obstacle detection through wireless sensing modules, which uses a microcontroller with information that allows determining the distance between obstacles and the user that is wearing the device. Moreover, it provides the user with tactile and auditory feedback related to this distance, enabling him to perceive the approach of objects or living beings, even without the ability to interpret visual signals. For this purpose, an experimental protocol was developed, which was carried out by visually impaired volunteers, with the approval of the ethics committee for studies with human beings (CAEE: 09844219.9.0000.5208), to assess usability and validate the prototype. The validation of the equipment was done through the statistical analysis of the results obtained from questionnaires applied to the volunteers submitted to the experiments. The results showed that 83.33% of the participants said they were at least satisfied with the mobility assistance provided by the prototype and 66.67% were at least satisfied with the confidence in the mobility promoted by the navigation assistant system developed in the first use of the equipment. The developed prototype was validated and its applicability as a navigation assistant for the visually impaired was verified. Ensuring easy use and freedom of movement, enabling improvement in the mobility of the individual.

Bionic hand is an artificial device used to replace an amputated limb. The myoelectric prosthesis have sensors able to acquire muscle signals from a electromyography devices, in which the signal is processed, features are extracted, and classified to be transformed in movements. This work presents the development of an active myoelectric prosthesis fully developed in CAD environment controlled using surface electromyography signals (sEMG). This process taking into account technical aspects like comfort, easy adaptation, improvement in self-esteem, with a low rejection developed using a 3D printing. The 3D manufacturing allows to develop custom projects, making possible to print prosthesis anatomically adapted. The control system used in this work was evaluated in open loop operation. This way, the control system presented accuracy in order of 92.5% in the execution of movements for healthy subjects. As for market analysis, the developed prosthesis presented a low cost comparing with the commercial prosthesis. Regarding the development aspects, their physical features presented a high robustness and innovative design.

Data communication over the electrical network (Power Line Communications—PLC) has become an alternative to other forms of communication, as it offers, among other advantages, the possibility of reusing the electrical infrastructure of environments. In the Establishments of Health Assistance (EHA), the PLC is also attractive because it does not emit high-frequency radiation, which can affect the imaging equipment. However, Brazilian EHA electrical installations are often neglect and it is not known whether PLC is possible. This work presents a micro-controlled system solution with PLC for evaluating communication at EHA, which uses a remote communication system with data storage platform. The system built-in hardware and software was able to perform real-time monitoring of packages over the PLC network, where it was verified that it is possible to carry out the sending and receiving of information without loss.

Understanding the functioning of behavioral mechanisms related to neuromotor adaptation is becoming crucial to idealizing improved rehabilitation. Motor adaptation is a trial and error process for adjusting movement to new demands, modifying the movement by attempting judgment based on feedback. To maximize performance, forces can be generated stochastic to disrupt movement, whether dependent on speed or position that destabilizes fluid movement, forcing a motor adaptation process. Given this reality, it is essential to explore how the motor adaptation processes occur so that you can learn to predict the sensory consequences of motor commands. In this sense, the objective of this study was to verify how, and if learning occurs when visual cues, in face of force field disturbances, are applied in predetermined trajectory movements, and these factors will contribute to the adaptation of sensorimotor behavior. From a serious game, associated with a robotic platform (based on the ‘H-man’ model) for upper limbs, 10 volunteers were evaluated while performing a movement segment containing force field variations and visual cues. about the intensity and direction of the field. It was realized that the learning process occurs independently and that for a single movement there may be more than one adaptation.

It is common to use TCP/IP (Transmission Control Protocol/Internet Protocol) for data communication through PLC (Power Line Comunications). However, for IOT applications the MQTT (Message Queuing Telemetry Transport) protocol has been used as an alternative to TCP / IP, as it is lighter, allows implementation on restricted hardware and works well on limited networks. In Brazilian Healthcare Establishments (HE), electrical installations often have maintenance and sizing issues, which can cause difficulties for PLC communication, mainly using TCP/IP. This work has implemented a MQTT network for PLC communication and performed tests on an HE to evaluate its functioning. The network was composed of two sensor modules and a server. The modules send information about the energy consumption of Medical-Hospital Equipment (MHE). The server displays graphics with the information arriving in real time and stores this information for later analysis. The tests resulted in the possibility of using the MQTT protocol for PLC communication in HE, even though the power grid is in unfavorable circumstances for this type of communication.

Wheelchairs play an important role in regaining lost mobility and in the social reintegration of its users. However, users with quadriplegia yet have a few low cost solutions that meet their needs. The present work proposes a shared control strategy designed to operate together with discrete human-machine interfaces, where the user has few commands, and capable to integrate different types of sensors that can be attached to a commercial powered wheelchairs, without the necessity of localization. Simulations show that the proposed strategy provides a robust and safe navigation through daily environments and does not take away the navigation autonomy from the user, who performs a fully-manual driving.

This paper presents the evaluation of a classical videogame for the assessment of people learning performance by identifying some deficient cognitive functions during matches. A pilot study was conducted to verify the feasibility to apply metrics to relate players behavior to deficient cognitive functions. We present a methodology where game data were collected from matches using the Game Learning Analytics (GLA) approach. Deficient cognitive functions were selected from Structural Cognitive Modifiability (SCM) theory. The obtained results at this pilot study pointed out to the feasibility of using established metrics in future work.

Instrumentation and control for automatic wheelchairs have diversified with technological developments that include non-invasive built-in sensors to capture body signals. The use of micro-electromechanical sensors (MEMS), tilt sensors, electroencephalographic signals (EEG), electromyographic signals (EMG) and cameras to detect movements of the head and hands have been included in the instrumentation of controllers to operate wheelchairs with the aim of improving the mobility of people with disabilities in lower or upper limbs, or in both regions. The goal of this work is to conduct a detailed review of articles about instrumentation and controllers based on body motion capture for automatic wheelchairs. The articles found develop different types of instrumentation for the safety of the user. Due to the inclusion and exclusion criteria, 30 articles that were published between 2003 and 2019 were analyzed. The controllers that implement head motion capture as well as their electronic instrumentation were given special attention in order to realize future developments. The designs that appeared in some articles demonstrated limitations due to specific user or location requirements, as well as offering solutions to these constraints. In conclusion, the controllers that receive information about body motion are useful for people with the aforementioned disabilities, resulting in greater independence and dexterity in the mobility of the wheelchair.

One of the main difficulties associated with the use of lower limb prosthesis is the perception of discomfort and pain in the residual limb, mainly due to poorly-fitted sockets. In this context, numerical simulations have performed a fundamental role in the search for successful fittings, contributing towards enhancement of the traditional iterative and labor-intensive fabrication process. This work aims to apply finite element modeling to simulate the socket-limb interface stresses for a transfemoral amputee during gait, and to investigate the effects of socket material and coefficient of friction on comfort and durability. The developed model was composed by socket, stump and femur geometries, and presented a loading scenario corresponding to the forces acting on the hip joint during a gait cycle. Several simulations were conducted, with varying design parameters, such that each configuration was analyzed in terms of prosthetic resistance to cyclic loading and distribution of contact pressures and frictional stresses. Carbon fiber sockets demonstrated greatest durability among the four tested materials, but it also induced a slight increase in the maximum contact pressure. As the coefficient of friction was incremented, contact pressures were reduced, and frictional stresses increased, with the values between 0.5 and 0.8 showing the best compromises.

This study presents subject specific lower limb joint angular kinematic and dynamic analysis at time and frequency domain as well as joint mechanical work, power and dynamic stiffness assessment during normal gait, stiff knee gait and slow running for indicative range operation of personalized active gait aid device. Gait aid devices present increasing interest for the generalization of gait rehabilitation, as an answer to the growth demand of population with gait rehabilitation need, as well as the insufficient health care personnel. Nevertheless, the large costs and standardized equipment leave out many patients without gait rehabilitation, with the need for low cost, personalized gait rehabilitation equipment, based on subject-specific analysis. In vivo and noninvasive case study was assessed of a healthy male subject 70 kg mass and 1.86 m height on human gait lab. Reflective adhesive marks were applied at skin surface of lower limb selected anatomical points and images captured with eight 100 Hz camera Qualisys along with ground reaction forces and force moments acquired at 2000 Hz with two AMTI force plates during foot contact with the ground on normal gait (NG) at comfortable auto-selected velocity, stiff knee gait (SKG) with lower knee flexion and slow running (SR) at minimum run velocity on stiff knee condition. Inverse kinematics and dynamics were performed using AnyGait with TLEM model and lower limb joint angular signal analyzed. Indicative range operation from lower limb joint mechanical assessment were obtained at complementary domain for subject specific gait aid device selection and parametrization.

Every year, strategies have been rethought in order to reduce the time of diagnosis and hospital stay, expanding the demand for care to patients of various pathologies, ensuring access to quality public health to citizens. This study aims to identify in the scientific literature the use of web/mobile tools in the management of information of cardiac patients from their hospital discharge (Phase II), until the end of the semi-assisted or face-to-face phases (Phases III and IV). Method: Search of articles in electronic journal databases available for access in the library system of the Federal Technological University of Paraná. Publications of newspapers, magazines, conferences and reviews were considered in the time interval from January 2014 to May 2020.

Patient-specific implants provide important advantages for patients and medical professionals. The state of the art of cranioplasty implant production is based on the bone structure reconstruction and use of patient’s own anatomical information for filling the bone defect. The present work proposes a two-dimensional investigation of which dataset results in the closest polynomial regression to a gold standard structure combining points of the bone defect region and points of the healthy contralateral skull hemisphere. The similarity measures used to compare datasets are the root mean square error (RMSE) and the Hausdorff distance. The objective is to use the most successful dataset in future development and testing of a semi-automatic methodology for cranial prosthesis modeling. The present methodology was implemented in Python scripts and uses five series of skull computed tomography images to generate phantoms with small, medium and large bone defects. Results from statistical tests and observations made from the mean RMSE and mean Hausdorff distance allow to determine that the dataset formed by the phantom contour points twice and the mirrored contour points is the one that significantly increases the similarity measures.

The digital image processing (DIP) techniques usually generate attribute vectors that tend to contain a large number of elements. When working with automated classification techniques, some commonly verified attributes may have low relevance for solving a specific problem or even worse the classification, unnecessarily increasing the dimensionality of the problem. A limited set of relevant attributes simplifies the representation of the image, and consequently, a better interpretation of the data occurs. In this perspective, this research applied Principal Component Analysis (PCA), a widely disseminated technique for reducing dimensionality in the literature, to the attribute vector generated by the DIP, with the aim of increasing the accuracy of the classification of this vector. As a case study, retinal image classification for the diagnosis of glaucoma was used. The data set used was the second version of RIM-ONE, provided by the Medical Image Analysis Group of the University of Laguna, Spain. The results showed that with the application of the PCA, a better classification of the images occurs. With only 7 components, a better classification was obtained than the original data set, which has 36 attributes. These results validate the possibility of applying PCA to optimize the automated glaucoma diagnostic process.

Cognitive load (CL) is the mental effort required to perform a task. It may be estimated by different ways, such as by electroencephalography, or analysis of pupil dilation (pupillometry). Due to the recent applications of CL for hearing aid performance assessment, this work presents a pupillometric system for CL estimation in speech intelligibility experiments. It consists of a one eye image acquisition sensor used in clinical video-oculography, and a signal processing software specially developed for recording pupil’s response and estimating CL. To overcome the adversities found in very low intelligibility conditions, a new CL index was proposed. Psychoacoustic listening experiments with 7 normal-hearing volunteers and noisy-speech compared intelligibility scores with pupil features for a wide range of signal to noise ratios (SNR). Preliminary results show a consistent increase of the proposed CL index with the SNR decrease. This index may be a useful tool for CL estimation in speech intelligibility investigation under very difficult listening situations. However, the observed findings are limited by the small testing group.

The human facial expression of emotions is an important way of nonverbal communication. Six facial expressions of emotions are considered distinguishable by the face image from a neutral expression: anger, disgust, fear, happiness, sadness, and surprise. Accurately recognizing and distinguishing these emotions is a complex and still an open research question. In this work, a deep convolutional neural network (CNN) is applied to extract facial expressions features from images. This CNN originates from a previously trained deep neural network (DNN). A multiclass support vector machine classifier (mSVM) replaced the fully-connected and softmax layers of DNN. One specific dataset is used to fine-tune the CNN; another dataset is applied to train the mSVM and assess system performance. The system reached an average accuracy of 92.1%. The happiness class got the highest classification performance with an F1 score of 98.9%. The lowest F1 score is 87.2% and belongs to sadness class.

Auditory Steady-State Responses (ASSR) are bioelectric potential evoked in the brain due to periodic auditory stimulation. An example of stimulus used to evoke an ASSR is the amplitude modulated tones, wherein the ASSR is characterized by an increase of energy at the modulation frequency of the electroencephalogram power spectrum. The presence or absence of an ASSR can be statistically determined by objective response detectors, usually implemented in the frequency domain through the Discrete Fourier Transform (DFT). To avoid spectral leakage in the DFT analysis, coherent sampling is often used. This technique consists of adjusting the stimulus modulation frequency so that an entire number of cycles occurs in an epoch of analysis. Thus, once the modulation frequency has been defined, other epoch lengths cannot be analyzed. This work proposes an objective response detector using the magnitude-squared coherence with least square and phase compensation to estimate spectral content, which does not require coherent sampling. This detector was analyzed in different epoch lengths and different type of windowing. For a small epoch, the new detector did not work because the false positive was not controlled. For large epochs, the new detector has lower detection rates. The best epoch lengths to use are the smallest possible ones before losing control of the false positive. For the data used in this work, the best epoch lengths were ranging from 256 to 512 samples. The tukey windowing was the most robust in terms of spectral leakage and presented the higher detection rate with false positive close to the significance level.

This paper presents a study by image processing to automate the thermogram analysis method of patients diagnosed with cancer. The objective is to develop a semiautomatic segmentation model of thermographic images using the Python computational language. A segmentation routine is proposed based on a region growth algorithm capable of grouping similar pixels to a Thermogram Region of Interest (ROI), starting from the manual positioning of the seed pixel, which is why the test is said to be semiautomatic. The tests were performed on twenty thermograms collected from patients with breast and thyroid cancer. As results it was verified that the proposed model comprises the tumor region with greater reliability than the manual delimitation method, thus the average and the minimum temperatures are higher (compared to the manual method) as it ensures that temperature points outside the real nodular range are not included in the ROI. As for operating time, the proposed method performs the ROI delimitation faster than the manual method. For future work, we suggest the statistical study for nodule benignity or malignancy based on thermal difference recorded in the ROI thermograms analyzed with the semiautomatic segmentation.

In the last years, surface electromyography (sEMG) has become a hot spot for research on signal classification methods due to its many applications with consumer grade sensors. Nonetheless, the correct classification of sEMG signals is not simple due to their stochastic nature and high variability. Our objective was to provide a comprehensive comparison between schemes used on the latest research, namely convolution neural networks (CNN) and hyperdimensional computing (HDC) using a public high-quality dataset. Our results showed that while CNN had substantially higher accuracy (68 vs. 32% for HDC, for 18 gestures), its shortcomings may be more prevalent in this area, as low amounts of training data, and lack of subject specific data can cause an accuracy drop of up to 70%/19% and 56%/7% for CNN/HDC, respectively. Our results point out that while HDC cannot reach CNN classification levels it is more versatile on small datasets and provides more adaptability.

Numerical models were developed to analyze the Eddy currents distribution in conductive volumes excited by time-varying magnetic fields. The sensitivity matrix was obtained for a defined topology of field generating sources and field measurement sensors. From the secondary field readings in a generator/sensor system, images of the conductivity distribution inside the material were obtained. The mathematical methods used to obtain numerical solutions for the inverse problem in magnetic induction tomography are presented. The result showed slight fluctuations in the object’s conductivity. This is because the high frequency components were eliminated in the image reconstruction program developed.

Monitoring vital signs remotely is essential for accident victims because any movement can aggravate their health state. This paper proposes to evaluate the feasibility of heart rate measurements using a video camera with the subject lying down to simulate an emergency situation. Plane-Orthogonal-to-Skin method (POS) was used to estimate the blood volume variation. The cardiac frequency was calculated using the Fast Fourier Transform (FFT) technique. Three body positions were chosen for the study: Ventral Decubitus, Dorsal Decubitus and Lateral Decubitus. The results demonstrated the possibility to obtain reliable heart rate values in these conditions with average Root Mean Square Error (RMSE) of 3.04 bpm. Future work aims to develop and evaluate an application for mobile devices that maintain the privacy of the examined subject.

This paper introduces an analysis about the Steady State Visual Evoked Potential (SSVEP) present in electroencefalogram (EEG) signals. This analysis was performed under some features. Firstly, the flickering stimuli varied along the 5.5–86.0 Hz range, and two types of settings were used, a monopolar and a bipolar. The analysis outputs were SSVEP amplitude response and its signal-to-noise ratio (SNR). These features were discriminated according to the three frequency ranges: low, medium and high frequency. Moreover, a subjective discomfort evaluation was performed through a questionnaire, which was answered by the 20 participating volunteers. Finally, it is shown that this study is in accordance with the literature statements about the SSVEP’s power and SNR behavior regarding the oscillating stimuli frequencies.

Studies have shown that subcutaneous fat thickness, muscle thickness, body mass index (BMI) and body fat percentage are all correlated with skin surface temperature (ST). It is known that anthropometric measures such as waist circumference (WC), Waist-to-Hip Ratio (WHR) and BMI are related to body fat percentage and that they can be useful tools to predict it. In this sense, the aim of this study was to analyze correlations between anthropometric measures and skin temperature, at rest and after a CrossFit® training workout. The sample was composed of 19 CrossFit® training practitioners (12 males and 7 females) with a 3-month experience minimum. Spearman’s rho correlation coefficient among anthropometric measures (BMI, WC, WHR) and all variables of temperature was calculated. Our results showed that, in resting conditions, waist circumference, BMI and WHR are not closely related with ST of limbs, thorax, abdomen and the back. After exercise, the most significant correlations found for men, except for one, were positive, while all significant correlations found for women were negative. It can be concluded that the correlations between anthropometric measurements and skin temperature are improved after physical exercise. The anthropometric measures studied (BMI, WC, WHR) showed moderate correlations with different body regions after exercise, in male volunteers. For females, WHR was the measure that best correlated with skin temperature after exercise, presenting strong correlations with 10 of the 26 ROIs studied.

This work presents an evaluation of the number of channel using an armband device for classification of hand gestures, aiming to reduce the feature vector dimensionality. Four classifiers and their optimized feature sets were used to recognize 6 gestures. Two search methods were applied to find the best channels: wrapper by Sequential Forward Selection and Binary Particle Swarm Optimization. Moreover, the data were organized in two approaches, analyzing the contribution of each channel and the contribution of each individual feature-channel. Each method resulted in different occurrences for the repeated channels, being the channels placed on flexor carpi ulnaris, palmaris longus, braquioradialis, and extensor digitorum muscles the most repeated. This analysis obtained an average of gain of 2 and a 60% of dimensionality reduction in classification, specially for the Support Vector Machine classifier, reaching 92.3% of hit rate with 9 inputs in Feature-Channel and wrapper approach. The applied methods indicate that there are some dependencies of features and channels in classification process. These dependencies could determine an ideal quantity of channels for a set of gestures and features not only depending on the classifier, but depending of the acquisition channels.

Smartphones are present in most people's daily lives. Sensors embedded in these devices open the possibility of monitoring users’ activities. The classification of the intricate data patterns collected through these sensors is a challenging task when considering hand-crafted features and pattern recognition algorithms. In this work, to face this challenge, we propose a convolutional neural network architecture along with two methods for transforming sensor data stream into images. The proposed model was evaluated using the UniMiB SHAR dataset. The best macro average accuracy obtained for classification of 17 types of activities, with fivefold-cross-validation-method, was 90.44%.

This paper proposes a bimodal biometric verification system based on face and voice traits. The face characteristics are extracted using an autoencoder neural network. The voice characteristics are extracted using Mel-frequency cepstral coefficients. The matching procedure uses the Euclidean distance between one sample and the cluster centers obtained for each subject, through a learning vector quantization machine. The data fusion process is done through a simple normalization and sum of individual scores of the face-trait and the voice-trait. Several experiments are carried out varying the number of cluster centers, the size of the encoder output and the number of frames used for representing the voice trait of a subject. The performance of the biometric system is evaluated using the area under a receive operating characteristic (AUC of a ROC curve). The following performances are obtained: voice-trait biometric system: AUC = 0.877; face-trait biometric system: AUC = 0.94 and bimodal biometric system: AUC = 0.98. The database used, the MOBIO, was collected from 50 individuals (37 male and 13 female) using mobile phones.

Global health rates show that breast cancer has remained at the top of the biggest causes of death among women. Radiologists use images such as ultrasonography to aid diagnosis. In the era of big data, in which there is a large amount of data available and the use of artificial intelligence is omnipresent in assisting activities, automatic diagnosis aid is a topic on the agenda. Convolutional neural networks are efficient in the most medical tasks. In this work, the performance of two convolutional neural networks, one with sequential architecture and the other with a direct acyclic graph structure, are contrasted for the task of automatic segmentation of breast lesions in ultrasound images. For the development and evaluation of the proposals, two image banks were used, containing a total of 550 ultrasound images. Performance metrics already established in the literature, such as Global Accuracy and Dice Coefficient, were used to evaluate the network architectures. The best segmentation result shows a global accuracy of 96%.

Cerebral Autoregulation (CA) is a intrinsic mechanism of the brain responsible for maintaining constant cerebral blood flow (CBF) despite the variation in arterial blood pressure (ABP). Transfer function analysis (TFA) is one of the most used signal processing techniques proposed to quantify this ABP-CBF relationship, by using spontaneous ABP oscillations to assess CA. The TFA is based on the concept that CA minimizes the effect of dynamic ABP fluctuations on CBF, which is reflected by the reduction in the CBF magnitude in the low frequency band and the phase of CBF related to ABP. Previous studies have assessed how different parameter settings in the TFA analysis have distorted its outcome, in order to understand the influence of each parameter variation. Currently, researchers at the Cerebral Autoregulation Network (CARNet) have concentrated efforts to standardize the TFA parameters used to quantify CA. In this context, this study aims to analyze the differences in the TFA indexes (gain, phase and coherence) varying its parameters in the Cerebral Autoregulation Assessment Open Source Platforman—CAAos (cross-platform toolbox for processing and analysing CA) such as window length, type and overlap in order to study the statistical similarities of its combinations. After all, the results are compared with the CARNet parameters setting in order to validate the CAAos platform as a valid tool for processing CA. The ANOVA test (Bonferroni’s post hoc test) applied over the TFA indexes for 5 healthy patients showed significant variations in the TFA indexes with the window length (particularly for 25 and 50 s) and type (Rectangular and Tukey), whereas overlap percentage variations resulted in no significant differences. The correct assessment of CA mechanism will improve our current understanding of the physiopathology of neurological diseases, as well as helping identifying patients with high-risk of cerebral hemodynamic disturbances.

The smaller the time window, the faster the response of a prosthesis to the user’s movement. However, very small windows have very little information, making it difficult to classify the surface electromyography signal (sEMG). This article presents the use of autoencoders for the detection of motion in real-time processing. For this purpose, a time window of 0.01 s window (i.e., ten samples per window). The difference between the number of peaks and the distance between them in the resulting latent space makes it possible to classify the moment when the patient starts to move. Through an autoencoder as an anomaly detector, it was possible to classify the beginning of the user’s movement, thus managing to improve the classification in real-time.

A computer-aided diagnosis (CAD) system is a tool to assist clinicians in interpreting medical images. In mammography, CADs provide a classification of tumors to distinguish between benign and malignant cases, aiming to support the clinical conduct. Nevertheless, CADs disregard informing about the internal criteria utilized to classify breast tumors, particularly, compatible with the Breast Imaging-Reporting and Data System (BI-RADS). In this context, we propose a new scheme of tumor classification based on the BI-RADS lexicon for masses. The terms of shape, margin, and density are modeled using specific feature sets to provide different perspectives of the tumor in terms of benign and malignant findings. The outcomes of the three models are further used for the final histopathological classification of the tumor. The proposed method is compared with two conventional CAD systems that classify tumors using a single feature set. The results show that the proposed method obtains 90% accuracy, whereas the two conventional CADs reach an accuracy of 89% and 76%. Therefore, the proposed method is suitable for the histopathological classification of tumors by using the information provided by the three models of the BI-RADS lexicon for masses.

This paper compares two approaches for semantic segmentation of breast tumors on ultrasound. The first approach, called conventional, follows the typical pattern classification process to extract hand-crafted features, followed by pixel classification with a Multilayer Perceptron (MLP) network. The second approach, called convolutional, uses a Convolutional Neural Network (CNN) to learn features automatically. For evaluating both approaches, a breast ultrasound dataset with 1200 images is considered. Experimental results reveal that the CNNs called VGG16 and ResNet50 outperformed the conventional approach in various segmentation quality indices. Thus, extracting hand-crafted discriminant features is challenging since it depends on the problem domain and the designer’s skills. On the other hand, through transfer learning, it is possible to adjust a pre-trained CNN for addressing the problem of tumor segmentation satisfactorily. This performance is because CNN learns general features in its first layers, and more subtle features are activated as depth increases.

This study presents a preliminary evaluation of using features linked to the Heart Rate Variability (HRV) extracted from the remote photoplethysmography (rPPG) signal to identify emotional levels (low, neutral and high) of arousal and valence. The method for obtaining the rPPG is a modified version of the sub-band algorithm and the Plane Orthogonal to Skin (POS) techniques. The emotion classification was evaluated in two forms: (1) personalized (or intra-subject); and (2) cross-subjects (or inter-subjects). The emotion-classification analysis were performed with feature vectors from HRV-based rPPG, and compared with the result from two traditional methods: the photoplethysmography (PPG) and the electrocardiography (ECG). The classification accuracy results indicate that: the proposed method cannot discriminate the arousal of the subjects, however for valence, the classifier got better results when rPPG is used, with accuracy of 51 % for personalized classification and 42 % for cross-subjects.

Classification is a crucial task in processing of surface electromyography (sEMG) signals. The Multi-Label Classification (ML) has gained prominence for biomedical applications, especially in gesture recognition for robotic prosthetic hand control. Differently of traditional method for classification involving three or more classes (multi-class), where each sample has only one output label, in the ML method, each sample may be referred to more than one output label. This work presents a pilot study of classification strategy using multi-label for hand gesture recognition. The methodology used to design the proposed system was the problem-transformation approach. The labels that compound the classifiers were developed based on the relationships of prosthesis operation and the anatomical nature of recognized gestures. In this way, it is easier to perform the motors of a prosthetic hand. The sEMG signals were obtained through the commercial Myo Armband (Thalmic Labs), in which data from 7 subjects were acquired performing 5 hand gestures. For the ML approach, the feature set was compound by L-Scale (LS), Maximum Fractal Length (MFL), Willison Amplitude (WAMP), and Mean Square Root (MSR). Nine classifiers were used, and the best classifiers with a accuracy of 97 and 98% with k-Nearest Neighbor (KNN) and Support Vector Machine with Radial Basis Function Kernel (SVMRBF). Regarding the single-label, no significant differences were observed between the multi-label tests.

The form of analysis of the cardiac signal most used today is the electrocardiogram (ECG). However, in addition to this form of data visualization, there is the vectorcardiogram (VCG), that allows a visualization of the signal in 3 dimensions. This study aims to compare the different ECG to VCG transformation matrices Kors and Inverse Dower (iDower), by analyzing some known parameters taken from VCG’s mathematically synthesized from 12-lead ECG’s of amyloidosis patients. The idea is also to compare that similarity for patients with different types of amyloidosis. The study was done through the analysis of electrocardiograms taken from a sample of 12 humans who have amyloidosis, either mutant or wild-type. The results indicated that there is not much similarity between the signals, although the similarity was higher for patients with mutant amyloidosis than for those with wild-type amyloidosis.

An accurate identification of schizophrenia is important for its early diagnosis and treatment. Due to the complexity and inherent heterogeneity of this disorder, an accurate marker has not been established yet. In this paper is proposed a new methodology for the detection of schizophrenia using EEG microstate analysis and graph theory. The proposed method, called Microstate Graphs, allows modeling and interpreting each microstate as a complex network, which permits to identify the effect of schizophrenia on some characteristics of the built networks. In an experiment carried out in a public dataset, the proposed method was useful to identify schizophrenic patients with an accuracy of ( $$91.67 \pm 2.06 $$ 91.67 ± 2.06 )% using an MLP trained with metrics extracted from microstate networks: assortativity, small-worldness, and local efficiency, indicating that the proposed method is promising.

The use of plane waves allows images with higher frame rates compared to conventional modes. Some studies have shown that the use of the Eigenspace Beamformer technique associated with the Generalized Sidelobe Canceler (EBGSC) reduces the effects of interference and noise, minimizing sidelobes and providing images with higher contrast and resolution compared to the Delay and Sum (DAS) and the Minimum Variance (MV) methods. Filters can also be applied after image processing to reduce speckle signals present in ultrasound images such as the Wiener and Kuan filter. This work presents the implementation of the EBGSC method with Wiener and Kuan filters to improve the processing of plane wave ultrasound images. The EBGSC method combined with Wiener filter (EBGSC-W) showed an improvement in the contrast of 70% and 57.2% when compared to the DAS and GSC methods, respectively. The geometric distortion was evaluated using the parameter of the full width at half maximum (FWHM) and the EBGSC-W also obtained a reduction in lateral FWHM by 63% and 25% compared to the DAS and GSC methods, respectively, approaching to the actual value of the target size (0.1 mm). The EBGSC method with the Kuan filter (EBGSC-K) showed improvements in the lateral FWHM, however, it worsened the contrast, with loss of information.

Electrical impedance tomography (EIT) is a technique that can be used to estimate resistivity distribution from the inside of a domain based on surface measurements. This could be useful, for example, in the diagnosis of cerebral strokes. However, a method to acquire EIT images of the head with enough quality to achieve this task is still needed. In this work, an automated method for the calculation of a statistical atlas of the human head is presented to be used as prior information for the ill-posed inverse problem associated to EIT. Fifty magnetic resonance images of healthy subjects were used for this purpose. Numerical simulations using a realistic head model with hemorrhagic and ischemic stroke were used to evaluate its effect. The results show that, when the atlas was used, there was a decrease in the root mean square error of the images obtained. Also, some artifacts observed in the image generated without the use of the atlas were eliminated or diminished. These findings hint to the possibility of using a statistical atlas of the head to improve the quality of EIT images.

The new ultrasound systems (US) based on the transmission of plane waves are able to generate videos with elevated frame rates when compared to the traditional techniques, allowing sophisticated exams. However, they generate a lot of data to be processed. Adaptive beamformer techniques are capable of reconstructing images with an elevate resolution, but with complex implementation and high processing demand. In this work it is suggested the use of a plane wave-based adaptive technique called Generalized Sidelobe Canceler (GSC). To evaluate the efficiency of this method with the decrease in the number of active elements of the transducer on reception, and consequent decrease in the amount of data generated, Sparse Arrays are considered. The evaluation of the proposed methods and comparison with the traditional method Delay and Sum (DAS) was performed using a simulated data set as well as in vivo collected data. The performance evaluation metrics were done using the Full Width at Half Maximum (FWHM) to check the lateral/axial resolutions, the contrast ratio (CR) and the and the Geometric Distortion Ratio (GDR). The results showed that the images generated by the proposed method, with a reduced number of active elements during the reception, were close to those provided by DAS in terms of spatial resolution and GDR, with the 65-element GSC method presenting GDR better than the DAS with 128 elements, indicating that the GSC method combined with proposed sparse arrays technique is suitable for imaging in B mode.

The Center of Mass (CM) plays an important role in balance assessments due to its physical definition. And the knowledge of its behavior provides information that may help the implementation of protocols to aid physiotherapy with a view of improving postural control capacities in some people. In this work, the kinematic method (segmental method) was used to estimate the human body CM, and this was only possible by knowing some joints locations in body. So, the Kinect device was used to provide the joints because its consistence and facility of use, also for its markerless method of recognizing human joints. After calculating all segmental CM by the anthropometric parameters and using the endpoints (joints), the total body CM was estimated. A male subject 1.67 m high and 60 kg mass participated of the initial test and a static task was performed to acquire data to the analysis. The subject remained standing still during 30 s in a comfortable standard position at about 2 m of the Kinect. The subject also performed a voluntary oscillation task. As result were obtained two graphs that represent the CM trajectory along the AP-ML plane (statokinesiogram) and the amplitude of CM displacement across time (stabilogram) and one graph representing the voluntary oscillation around the ankle. The results also showed the CM location in percentage being 57.56 ± 0.10, that can be compared to the physiological CM being 55%, what is quite good estimation. Therefore, the potential of this low-cost photogrammetric device is noticeable to compose a method of CM estimation and also for studies in balance assessments.

The directed transfer function (DTF) is a measure based on the concept of Granger’s causality, which associated with a neurofeedback system, can represent an important analysis tool to support the treatment of neuropsychiatric disorders. Defined in the structure of the multivariate autoregressive model (MVAR), the DTF provides a spectral estimate of the strength and direction of any causal link between the signals acquired by electroencephalography (EEG). This study aims to estimate the directed functional connectivity related to the attention status of healthy adult individuals during neurofeedback sessions, aiming to better understand how the neuronal regions communicate and influence each other’s activity and study the feasibility of using these algorithms with neurofeedback. Data were collected from 19 individuals, eleven male and eight female, with an average age of 21.21 years, standard deviation of 2.39 and an age range of 18–26 years. As a result, they were able to identify changes in the direction and strength of the interaction flow between certain brain regions that occurred during the sessions, suggesting that the sessions enabled individuals to activate brain regions related to the state of attention. The main contribution presented in the study was the use of the mathematical methods mentioned to identify and analyze brain modulations in individuals who participated in neurofeedback sessions related to the strengthening of the state of attention.

This work aims to apply recurrence quantification analysis to characterize electroencephalogram signals, in resting and active state situations involving mathematical operation resolution. The best values of the incorporation parameters (delay time, embedding dimension, and threshold) are investigated to obtain the best ranking results. The measures of the recurrence quantification analysis used are recurrence rate, determinism, overage length of diagonal structures, Shannon entropy, laminarity, and maximum length of vertical structures. To compare between resting and active state, the Mann-Whitney test was performed. The results demonstrate that the resting state is predominant in the alpha and theta experiments. Statistical differences were observed in the comparisons between resting and active state for alpha and theta experiments, active state alpha and active state theta experiments and resting and active state for theta experiments.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder, affected by persistent deficits in communication and social interaction and by restricted and repetitive patterns of behavior, interests or activities. Its diagnosis is still a challenge due to the diversity between the manifestations of autistic symptoms, requiring interdisciplinary assessments. This work aims to investigate the performance of the application of techniques of extraction of characteristics and machine learning in magnetic resonance imaging (MRI), in the classification of individuals with ASD. In MRI, the techniques of features extraction were applied: histogram, histogram of oriented gradient and local binary pattern. These features were used to compose the input data of the Support Vector Machine and Artificial Neural Network algorithms. The best result shows an accuracy percentage of 89.66 and a false negative rate of 6.89%. The results obtained suggest that magnetic resonance analysis can contribute to the diagnosis of ASD from the advances in studies in the area.

The discriminant linear analysis algorithm is a statistical tool, without iterative training, capable of determining the best data projection reducing the characteristics dimension size to a new space. The new space contains a dimension number equals to the number of input classes minus one. In the specific case of two input classes, the resulting space projection will be a one-dimensional space where a simple threshold classifier is able to determine that a sample belongs to one or another class. This paper explains the theory and also this special case, applying the technique on biomedical data like pulmonary crackles characterization, and detection of spikes in EEG signals. Besides machine learning techniques, statistical analysis proved to be a simple, fast and efficient way to classify patterns.

Physical exercise induces the thermoregulation process of the human body, in order to avoid overheating produced by muscle contraction. The infrared thermographic image (ITI) is an option to assess the change in body temperature, as it monitors the physiological functions related to the control of the skin surface temperature in real-time. The aim of the present research was to verify the effectiveness of infrared thermography as an instrument for monitoring the central body temperature through the facial thermal behavior of individuals pre, post and 24 h post-CrossFit® training workout. This study evaluated 10 adults’ volunteers of both sexes, physically active, practitioners of CrossFit®, with a body mass index of 23.79 ± 2.66 kg/m2. The training consisted of typical exercises of the modality CrossFit® and lasted 50 min. The athletes were monitored for 24 h, with acquisition of facial thermographic images in the Pre-Workout, Post-Workout moments and 24 h after training. The maximum (Tmax) and average (Tmed) temperatures were chosen to analyze the results, both for the front and side views. There was no difference in skin temperature between the regions of interest (p > 0.05), both for Tmax and Tmed at different times. It can be concluded that thermography is a tool for monitoring the central body temperature, through the facial thermal behavior, of individuals during a CrossFit® training, and also that the CrossFit® practitioners evaluated presented a good thermoregulation capacity, managing to effectively dissipate the heat produced in the training after 24 h of evaluation.

This paper presents an implementation of an approximate analytical solution for the wave equation in one and bidimensional domains for Dirichlet Boundary Conditions (DBC), i.e., the primary variable is known in the domain boundary and it is defined as a periodic function of time. The approximated solutions are derived using Fourier series and are implemented in Python 3.7 programming language according the Object-Oriented Paradigm (OOP), providing flexibility for increasing the number of terms and several visualization tools. The presented results are compared with the Finite Difference Method (FDM) solution for the wave equation, leading to root-mean-squared-errors of order of $$10^{-3}$$ 10 - 3 .

This project aims the implementation of an approximate analytical solution for the wave equation in one and two dimensional domains for Neumann Boundary Conditions (NBC), which the gradient of the primary variable is known within the boundary domain and, for the proposed implementation, is defined as a periodic function of time. Fourier series was used to determine the approximated solutions for the wave equations and it was implemented in Python 3.7 programming language. The Object-Oriented Paradigm (OOP) approach was used to provide flexibility for the implementation, resulting in an Application Programming Interface (API) that provides functionalities such as increasing the number of approximation terms and several visualization tools. The results are presented considering two different frequencies and compared to the Finite Difference Method (FDM) solution, leading to root-mean-squared-errors of order $$10^{-6}$$ 10 - 6 (Pa).

Due to increase demand for magnetic resonance imaging (MRI), there was a need to attest to the quality of exams with quality certification. In the area of diagnostic imaging, several services seek certification. The interested institution must ensure that the minimum standards required are met. Thus, this study aimed to analyze and compare the parameters of MRI exams at a Center for Image Diagnosis in Curitiba/PR, Brazil, in relation to the guidelines of the Imaging Diagnostic Accreditation Program (PADI), for the evaluation and readjustment of the standardization for the accreditation process. Examination images from the musculoskeletal system were collected and recorded in Digital Imaging and Communications in Medicine (DICOM) form, as is the submission standard for the accrediting organization. For this article, the results of the cervical spine exam were selected, following the sequence planning and routine protocol. Then, the results were compared to the literature in the area and to the guidelines of the accrediting organization, PADI, regarding four evaluation points: mandatory minimum sequences, image contrast, anatomical coverage and spatial resolution. In the conformity assessments, the protocols were shown to be within the established standards and apt to be accredited.

In this paper, we propose a classification technique for melanocytic lesions based on fundamentals of Information Theory. In particular, we evaluate the accuracy level of the Correntropy Coefficient as a similarity measure in classifying Melanoma and (common and atypical) nevi. These lesions were chosen because they are generally similar to each other, then it can be difficult to carry out a differential diagnosis of the melanocytic lesion type. The effectiveness of the proposed approach was verified through a case study using a public dermoscopic image dataset. The obtained results for performance evaluation and comparison show very high accuracy for melanoma classification which outperforms state-of-the-art approaches. Besides, considering the simplicity of the proposed technique and the results obtained, it is possible to use this approach in developing computational systems to support the medical diagnosis of melanomas.

Cancer is the second most common cause of death in the world. Several treatments are used against this disease. Chemotherapy is a drug treatment against cancer, but it is a slow process with several side effects. Electroporation (EP) is a technique that allows increasing cell permeability by applying high-intensity electrical pulses for short periods and can be used to speed up the chemotherapeutic process, resulting in Electrochemotherapy (ECT). ECT is a well-known technique for the treatment of superficial tumors and is being developed for deep-seated tumors. Pre-treatment simulations are reasonable solutions to predict whether the electric field intensity will be high enough throughout the tumor mass. This article presents a software development to segment and to export biological 3D structures from a medical image to an electric field simulator. A realistic lung tumor was in silico studied using ECT with electrodes proposed by the ESOPE protocol. The results demonstrate that multiple applications of the electrodes eliminate the tumor. Evaluation of the required electric current and electric field distribution allows the development of new electrodes and equipment in real applications of ECT treatment.

Medical images are a powerful tool to help the physicians in diagnosis and planning a surgery. Ultrasound (US) and Magnetic Resonance Image (MRI) are the most used techniques in the literature with this purpose. Both have their positive points and negative points related to the quality of the image acquisition, some parameters which are looked for are if the same technique, or combination, can give a high-quality definition of the position and fast acquisition of the image. With this worry in mind, this work has the aim to answer a specific question: “Which are the characteristics of ultrasound and magnetic resonance image registration methods for interventional procedures?”. We used the PICOS (Problem, Intervention, Comparison, Outcome, Study) tool to define the search. As the inclusion and exclusion criteria were the year range (from 2013 to 2019) and if the study applied both US and MRI for image registration. As a result, 22 out of 96 articles matched the criteria. It was observed that Urology, Neurology, Hepatology, Cardiology and Gynecology are the medical fields in which the US and MRI combination are most used. There was a preference by the authors for the use of non-rigid transformations for recording US and MRI images. This fact can be justified by the need to consider the difference in the shape of structures in the US and MRI images for registration. The accuracy was the most used metric in the evaluation of image recording methods. The metrics used to assess accuracy varied according to the study field.

A brain-computer interface (BCI) based on the steady-state visually evoked potentials (SSVEP) paradigm deals with the challenge of determining the frequency associated with the visual stimulus the user is concentrated on, given electroencephalography (EEG) recordings of the brain activity. For this, the BCI process the brain signals in order to remove artifacts and, more importantly, to extract relevant features that contribute to the classification. A technique known as autoencoder (AE) has gained special attention in the last decades due to its ability to discover advantageous representations for a dataset, even with a significant dimensionality reduction. Essentially, autoencoders (AEs) are neural networks composed of two parts—encoder and decoder—whose roles are, respectively, to create the internal representation (named code) for the input data, and to reconstruct the input data from the generated code. Thus, the encoder corresponds to a powerful nonlinear feature extractor. In this work, we investigated the use of AEs to perform the feature extraction in a BCI-SSVEP. Different AE approaches have been analyzed, both in time and frequency domains, considering two classifiers: logistic regression and support-vector machines. The obtained results reveal that AEs can offer a performance improvement when compared with a BCI using the discrete-time Fourier transform (DFT) features.

Heart diseases are the cause for many of the human deaths in the world. A reasonable part of the population is affected by heart diseases. A primordial health monitoring to the diagnosis of heart illness is the electrocardiogram. The signal of the heartbeats captured in this protocol is key for medical professionals to investigate if the individuals are healthy or suffer from some possible heart disease. In this paper, the LPC technique is proposed to the automatic heart rhythm estimation. The QRS complex can have a variety of formats depending on the sensors positioning or even be hard to discriminate in a visual inspection of the signals or conventional threshold detection techniques. The signals are then filtered by a single, low order LPC filter, and the absolute value of the error estimation can be easily used in a threshold detection scheme to estimate the beats per minute heart rhythm. A database subset taken from MIT is used to test the efficiency of the approach. The direct measurement from the signals is presented to give a fair comparison of the findings.

In this paper, a compression method for electrocardiographic (ECG) signals is proposed. The proposed method is based on the spectral content variation of each cycle of the ECG signals. The fast Fourier transform (FFT) is used as the signal spectrum estimator. The proposed method allows the entire reconstruction of the ECG waveform signals from the compressed data, keeping all relevant information present in the original signal for further diagnostic analysis and processing. In order to show the credibility of the method, a visual inspection by a cardiologist was done on the reconstructed signals.

People with transtibial amputation, the stability is altered as a consequence of body part removed, including: the bone elimination, muscle tissue and somatosensory information and this causes transtibial amputees to have a high number of falls. It is necessary to know static stability and the indicators corresponding to this type of amputees, since it directly influences postural stability and the performance of various activities, including displacement, which directly affects the rehabilitation. Likewise, the information on stability in transtibial amputees is insufficient, and in amputees by land mines is null, the affectation suffered in the pressure center (COP) due to the type of amputation is unknown. A cross-sectional observational investigation was carried out in transtibial amputees due to trauma from landmines, people without amputation were also included, the COP was recorded in both groups to assess the upright position using the Romberg Test. Recorded data from amputee subjects differs significantly from non-amputee subjects. The first one shows an increase in biomechanical parameters related to stability, demonstrating that they make continuous use and more frequently compensation strategies to preserve stability when standing.

This study presents and applies in vivo lower limb frequency response analysis during standard maximum vertical jump (MVJ) with long and short counter movement (CM) and corresponding muscle stretch shortening cycle (SSC) for comparison without CM and SSC condition. The study makes use of algebraic relation at the frequency domain to obtain the response function from the input and output signals. Single-input/single-output (SI/SO) constant parameter linear system (CPLS) was applied with vertical ground reaction force (GRFz) input and center of gravity (CG) vertical displacement ( $$\Delta z$$ Δ z ) output, obtaining lower limb frequency response function during MVJ impulse phase. Piecewise linearity and limited input-output range of experimentally acquired GRFz and CG $$\Delta z$$ Δ z during MVJ impulse phase were assessed to confirm assumptions for CPLS application. Piecewise stationarity of the input and output signal was ensured by acquiring those signals on each MVJ type at similar conditions, guaranteeing experimental repetitions under statistical similar conditions on each CM. Different CM condition on each MVJ type were compared as regards to maximum vertical height, time period of the impulse phase, fundamental harmonic frequencies, convergence of the GRFz input and CG $$\Delta z$$ Δ z output Fourier series, their autospectral and cross-spectral density, as well as its input-output coherence, cross-spectrum gain factor, and phase of the frequency response function. Several differences were detected among CM condition, potentially contributing to explain differences on achieved performances at each CM and SSC.

Continuous monitoring of brain hemodynamics is important to quickly detect changes in healthy cerebral blood flow, helping physician decision-making in the treatment of the patient. Resistivity changes in the brain happen as a result of the pulsatile characteristic of the blood in the arteries or pathological conditions such as ischemia. We developed a dynamic model of cerebral circulation capable of portraying variations in resistivities in arteries within a cardiac cycle. From the hypothesis that the resistivity changes in the brain can be detected by Electrical Impedance Tomography (EIT), we included this model as prior information in time-difference image reconstruction algorithm. With this prior information, image reconstruction of the brain with pre-existing ischemia was possible, showing that EIT is a potential technique for brain hemodynamic monitoring.

The high-density electromyography (HD-sEMG) is a non-invasive technique to measure muscular activity using grids of surface electrodes, being used to evaluate neuromuscular disorders. Therefore, the present work is aimed to develop a MATLAB-based graphical user interface (GUI) for HD-sEMG signal analysis. As input, the user uploads the HD-sEMG and force signals, acquired during a sustained contraction. The parameters calculated are: (a) amplitude estimators: average rectified value (ARV) and root mean square (RMS); (b) frequency estimators: mean frequency (MNF) and median frequency (MDF); (c) topographic maps estimators: coefficient of variation (CoV) and modified entropy (ME). Both the HD-sEMG, force, and the parameters are calculated along time intervals and presented in graphs. The topographic map that represents the muscular electrical activities under the electrode’s array location is also demonstrated within the GUI. To assess the reliability of the developed interface, the RMS and MNF parameters were used to compare the values obtained by the developed interface and the commercial interface OT BioLab+. A perfect degree of reliability (ICC = 1) was found for the RMS and MNF variables.

The disk diffusion method is one of the most frequently used techniques to determine the antibiotic susceptibility profiles of pathogens. A fast identification of resistance profiles is essential for researchers and physicians. In laboratories without technological resources, these measurements are done manually using a ruler or a caliper increasing the chances of error. We have designed a device that, by mean of image processing of disk diffusion tests, semi automatizes the process. A total of 53 images of plates containing, on average 11 inhibition zones each were acquired and we compared the results obtained by the proposed algorithm with the results from the commercial equipment Osiris® (considering the correction in the measurements made by a human operator). The proposed algorithm correctly identified the position of the 597 inhibition zones in 100% of the images. The Pearson correlation coefficient between the measurements of the inhibition zones diameters by the proposed algorithm and our reference was 0.7728. The Cohen’s kappa coefficient between reference and the proposed method was 0.729, and the concordance between methods was 86.3%, where the most significant error rate was 0.2%. This study was approved by the HCPA Health Ethics Committee under number 170587.

Ketogenic diet (KD) is used to loose weight and in the treatment of epilepsy due to its anticonvulsant properties. Evidence demonstrates that this diet can assistant to diminish inflammation and reduce mortality, even though the genetic and molecular mechanisms are not yet well understood. This article investigated the gene expression under KD searching for differentially expressed genes and biological networks. Three publically available microarray datasets of mouse liver have been analysed and reported differentially expressed genes and Gene Ontology categories that are statistically overrepresented. Differentially expressed genes were filtered for adjusted p-value 0.05. The intersection between the three datasets revealed only 2 genes. To identify robust response (2 out of 3 datasets), the union of the intersection of the differentially expressed genes was calculated and revealed 33 genes, which were used to evaluate the Gene Ontology categories overrepresentation and Functional Profiling using gProfiler with KEGG Orthology. According to the results found, a KD has a fundamental role in the release of ketone bodies, mediated by PPAR $$\alpha $$ α , influencing metabolism process.

The aging process makes changes in the cardiovascular structure, increasing the risk of diseases, making people more dependent and vulnerable. The Brazilian National Institute of Social Security points out that every year around 250 thousand new cases of stroke are documented in Brazil, around 40% of retirement requests are due to heart attacks or strokes. Heart diseases are one of the most prominent causes of death in the world. The majority of sudden death cases occur without previous symptoms, while some non-lethal arrhythmia’s such as ventricular extra-systoles precede others directly related to it. With that in mind, it is advisable to monitor high risk individuals, who are not hospitalized, on a daily basis. Considering the aging of the population and the increasing number of people living alone, due to it remote monitoring systems, for various types of biomedical signals, are important. The goal of this paper is to evaluate two approaches of QRS classification using the BIH-Arrhythmia Database comparing the performance obtained on each. The algorithms tested were: J48 and Multilayer Perceptron, one of the approaches of this work obtained the weighted average Sensitivity 96.91% and Precision of 96.81% for J48 and 94.77% Sensitivity and 93.87% Precision for MLP.

The diagnosis based on mammography depends on relevantly upon the radiologist’s experience and accuracy in identifying shapes and tenuous contrast in the images. A possible improvement in the mammography consists of image analysis algorithms suitable for detecting and segmenting tumors. However, such an approach usually demands high computational processing. In this context, the present work objective was to develop an algorithm to accurately search and segment tumors in mammography images without requiring high processing power. Thus, efficient, low computational demanding, and automatic image segmentation occurred by performing traditional image processing, including uniform equalization, adaptive enhancement (CLAHE), simple thresholding, Otsu multiple thresholds, and morphology operators. The development of the algorithm divides into two steps. The first step was the isolation of the breast and removing the pectoral muscle. The breast isolation occurred by removing artifacts outside of the breast image. The pectoral muscle removes as this region presents gray levels similar to the tumor. Finally, the second step segmented the tumor mass. The algorithm validation occurred by determining the accuracy and the Dice similarity coefficient, which values (mean ± standard deviation) were, respectively, 0.75 ± 0.09 and 0.71 ± 0.11. These average values resulted after processing 150 images of the CBIS-DDSM database, signifying a good segmentation outcome. As for the processing speed, the algorithm spent 14,5 s to segment a tumor in an image sizing 5383 × 3190 pixels (16 bits), using a conventional computer. The tool was able to segment both tiny and large tumors, and it may represent a convenient approach to assist in the analysis of mammograms without requiring high computational resources.

The classification of surface electromyographic signals is an important task for the control of active upper-limb prostheses. This article aims to analyze and evaluate techniques to classify surface electromyographic signals for the control of upper limb prostheses. The electromyographic signals were obtained from a public database. Machine learning algorithms and seven features of the EMG signal were used to classify the signals. Random samples were created for the training and testing tasks in subsets with 80% and 20% of the data, respectively. Machine learning algorithms for classifying electromyographic signals were trained with different configurations, allowing evaluation between combinations of techniques and parameters. It was observed that signal feature extraction is an important process for obtaining accurate results. The best result produced an average accuracy of 95% with a Random Forest classifier and three features extracted from surface electromyography signals of two channels.

Signals derived from brain activity can be used as commands to control an external device or application in Brain-Computer Interface (BCI) systems. Electroencephalography (EEG) is widely used to record brain signals due to its non-invasive nature, relatively low-cost, and high temporal resolution. BCI performance depends on choices regarding available options for signal pre-processing, classifiers, and feature extraction techniques. In this paper, we describe the use of an Artificial Neural Network (ANN) based on a Multilayer Perceptron (MLP) architecture as a classifier to identify motor imagery tasks using EEG signals from nine subjects of an experimental data set. BCIs based on brain signals recorded during motor imagery tasks use the changes in amplitude of specific cortical bands as features. Moreover, we evaluated the effect of systematically decreasing the number of inputs (EEG channels) on the classifier performance. The results show that a MLP classifier was able to segregate the EEG signature of four motor imagery tasks with at least 70 $$\%$$ % accuracy using at least 12 EEG channels.

Individuals with spinal cord injuries lose the ability to complete hand movements. Active orthosis based on myoelectric signals may provide a more intuitive control from the remaining muscles. Pattern recognition has been widely used to detect the intention to control assistant devices for rehabilitation, but little work has been extended to injured individuals. This work presents a proposal for real-time detection of hand movements based on myoelectric signals. A subject with incomplete spinal cord injury at the cervical level attempted to elicit flexion/extension fingers and resting while two-channel electromyographic signals were acquired. A classic on–off control was compared with different configurations of KNN, yielding classification performance up to 81.00% in real-time. The results showed the ability of the subject to performed contractions with repeated patterns for the control of low-cost active orthosis.

Functional connectivity (FC) analysis has been widely applied to the study of the brain functional organization under different conditions and pathologies providing compelling results. Recently, the investigation of FC in motor tasks has drawn the attention of researchers devoted to post-stroke rehabilitation and those seeking robust features for the design of brain-computer interfaces (BCIs). In particular, concerning this application, it is crucial to understand: (1) how motor imagery (MI) networks dynamics evolve over time; (2) how it can be suitably characterized by its topological quantifiers (graph metrics); (3) what is the discrimination capability of graph metrics for BCI purposes. This work aims to investigate the MI single-trial time-course of functional connectivity defined in terms of event-related desynchronization/synchronization (ERD/S) similarity. Both ERD/S and clustering coefficient (CC) underlying FC were used as features for characterizing rest, right-hand MI, and left-hand MI for 21 subjects. Our results showed that MI can be associated with a higher CC when compared to rest, while right- and left-hand MI present a similar CC time-course evolution. From the classification standpoint, ERD/S, CC and their combination provided moderate to substantial single electrode peak performances (in terms of Cohen’s kappa) for discriminating rest and movement, i.e. for identifying alpha rhythm suppression. Weak peak classification performances were achieved for these features for right- and left-hand discrimination, but the combination of FC-based features and ERD/S provided significantly better results, suggesting complementary information. These results illustrate the symmetrical nature of brain activity relative power dynamics, as reflected in dynamics of functional connectivity during single trial MI and motivate need for further exploration of such measures for BCI applications.

Wearable devices for human activity recognition (HAR) provide continuous remote health monitoring, which can offer many benefits for patients in rehabilitation, the elderly, and even the population in general. Those devices handle a big amount of data and run complex algorithms for delivering information with precision to the user. However, to achieve a satisfactory performance in terms of energy consumption, real-time response and privacy, the solution needs to be efficient and suitable for running in resource constrained devices. Many HAR proposals use deep-learning approaches for achieving almost perfect performance, nonetheless those techniques are not convenient for embedded solutions. To meet the demands of high precision and low power, more efficient strategies can be developed and optimization techniques can be applied to the usual deep learning approaches. We present in this paper a lightweight model for HAR based on two-level classifier and using a compact, pruned and quantized convolutional neural network. We obtained accuracy and F1-score above 90% with an extremely lightweight solution and intended for use in embedded systems.

Therapeutic procedures capable of evaluating and positively intervening in the reduction of anxiety disorders is essential, and Functional Neurometry is a good option. In this method, neurophysiological signals emitted by the human body are captured to assess and train the behavior of the patient. This study aimed to evaluate the applicability of Neurometry in the Assessment of Anxiety Levels in undergraduate students from the Psychology course of a private educational institution. Thirty students participated in this controlled and randomized clinical trial including 26 female and 4 male students. The experimental protocol involves the application of 4 instruments: sociodemographic and lifestyle questionnaire; Beck Anxiety Inventory (BAI); salivary cortisol measurement; and Neurometry applied according to the sound anxiety protocol (SAP). The interventions were carried out in two different stages (time cuts): in the first assessment, all 4 instruments were applied for each student. They were done when the students were busy with semester evaluations, finishing internships, and making practice reports. At the second assessment, they were returning from vacation, and only the BAI and neurometry protocol were applied. In stage 1, only 4 students (13.4%) had salivary cortisol levels above the reference value. For BAI, 16 students (53.3%) showed severe anxiety. In terms of neurometry protocol, 13 students presented level 5 (anxiety control in the exhaustion phase or physical and psychological exhaustion to stress). In stage two, the severe anxiety index fell for 13 students (43.3%), while the index 5 (anxiety control in the exhaustion phase/physical and psychological exhaustion due to stress) appeared for 12 students (40%). The results obtained point to neurometry as an efficient instrument for measuring anxiety levels.

Measurement of blood pressure is critical for patients with cardiovascular disease. Using a cuff sphygmomanometer with non-invasive registration is currently the most common practice since its fast and does not require an experienced operator. However, it does not allow continuous pressure monitoring and the discomfort of the procedure can discourage consistent use. Photoplethysmography (PPG) is a technique increasingly used for non-invasive, portable devices to monitor arterial oxygen saturation (SpO $$_2$$ 2 ), heart rate and, more recently, for glycemic control. In this study, we evaluate different methods to estimate blood pressure using PPG. Two methods presented are adapted from the literature, while the third is an improvement proposal. Multiple linear regression (MLR), artificial neural network (ANN), support vector machine regression (SVR) and decison tree regression (DTR) using temporal and spectral PPG features are evaluated. Principal component analysis (PCA) is used in order to reduce dimensionality. The MIMIC (Multiparameter Intelligent Monitoring in Intensive Care) database is used to train and evaluate the approaches. Results indicate that the proposal improves diastolic (DBP) and systolic (SBP) blood pressure estimation with mean absolute errors (MAE) of 6.52 ± 5.75 mmHg and 13.19 ± 11.90 mmHg, respectively.

Resting-State functional magnetic resonance imaging (rs-fMRI) provides the assessment of some brain functions without tasks. Through rs-fMRI, it is possible to discover that the brain is organized in spatially distributed and interconnected brain regions. Studies suggest that aging and certain neurological or neuropsychiatric diseases affect brain connectivity, such as Alzheimer’s disease (AD) and mild cognitive impairment (MCI). The general objective of this work is to investigate the evolution of the brain connectivity of individuals with healthy aging who convert to MCI and individuals with MCI who convert to AD, using rs-fMRI and analysis based on graph theory (GT). The processing was implemented in SPM12-MATLAB, and the analysis was performed in the CONN Toolbox. The GT metrics chosen to describe the main topological characteristics of the networks were: characteristic path length, global efficiency, local efficiency, clustering coefficient, and degree. Two main findings emerged from this study. When using GT metrics and analyzing healthy subjects converting to MCI, it was possible to observe a decrease in all GT metrics. Second, changes in GT metrics indicated a rupture in the functional connectivity when the cognitive decline occurs from healthy aging to MCI and from MCI to AD.

The cultivation of cells in 3D has gained more interest in research once 3D architecture can be closer to full cell physiological functionality. The cultivation of the cells in a spheroid format has shown very promising results, further for bioprinting developing so fast during the last decade. The interaction of spheroids and the matrix, or bioink, have provided new structures to be analyzed, specially if one would like to follow the whole system (spheroid and bioink) without fluorescent dyes. Trying to solve this image limitation, the aim of this paper is to present a study on different Convolutional Neural Networks (CNN) architectures employed to identify different structures in fibroblast NIH-3T3 spheroids. Three different architectures were considered: GoogleNet, ResNet18 and AlexNet, all implemented in Python 3.7 using the PyTorch Application Interface Programming (API). Given a spheroid image taken in a light microscope, four structures can be identified: the cell, the dead cell, the impurity/contamination and the background consisting of a gel in which the spheroid is immersed. All four CNN architectures were trained and evaluated with a dataset consisting of over 370 samples, split into a training set ( $$\approx 70\%$$ ≈ 70 % ), a test set ( $$\approx 20\%$$ ≈ 20 % ) and a validation set ( $$\approx 10\%$$ ≈ 10 % ). Since our dataset has unbalanced classes, a data augmentation was applied in order to provide a comparable number of samples for all classes being considered.

EEG—Electroencephalogram is the register of the brain activity, usually obtained from a non-invasive method that uses metal electrodes connected on the subject scalp, according to International 10–20 System of Electrode Placement. The analysis of an EEG signal can reveal a patient’s state of healthiness related to some neurological disorders, such as Alzheimer, Parkinson and Epilepsy. In this paper an artificial neural network with dynamic sampling strategy of an EEG signal based on backpropagation algorithm for recognition of brain waves in Alpha, Beta, Theta and Delta patterns was implemented with accuracy of 95%. As these waves are related to the usage of brain regions involved according to the instant task and its specificity, such as cognitive tasks, spelling and writing tasks, sport practices tasks or even resting, the result of its recognition followed of qualitative analysis can be used for applications in diagnosis of neurological diseases.

This research exposes a different method for the analysis of ultrasound images (US), aiming to increase the diagnostic possibilities of this exam. The advances in the development of techniques that assist in medical diagnosis are constant, and, among them, the panoramic ultrasound has provided an image analysis with a greater field of view. This method could propose that patients to other diagnose options, free of ionizing radiation, and at a lower cost. The exam images were obtained at the University Hospital of the Federal University of Pará (Brazil) and treated to analyze female organs in the pelvic region, the organ chosen in this study was the bladder. This research analyzed images around the patient's pelvic region: images obtained with the translation of the ultrasound transducer in a 360º trajectory. In this study, the ultrasound images were pre-processed, segmented, and reconstrued. Although this study is in its initial phase, it is possible to obtain panoramic images of the pelvic region and make the bladder reconstruction. However, further development of technique is necessary to obtain more precise and specific results.

Functional connectivity between surface electromyography (EMG) signals is still an unexplored area, mainly the study of directed coupling. The Partial Directed Coherence (PDC) technique has been used to analyze the direction of information flow on muscle networks. This work aims to use PDC to investigate the information flow during hand movements. The EMG signals were acquired from six muscles of the hand and forearm of 10 participants, during extension (FE) and flexion (FF) of the fingers. The average of PDCs was calculated and displayed as color maps. Two frequency bands were analyzed, 10–60 Hz and 60–400 Hz. In addition, the prevalence of flow direction between a muscle pair was inferred by paired Wilcoxon Non-Parametric Test. The results for FE movement showed a consistent direction of information flow from the First Dorsal Interosseous (FDI), Flexor Digitorium Superficialis (FDS), and Flexor Digitorium Profundus (FDP) to the Digitorum Extensor (ED). On the other hand, for FF movement, the coupling direction was from FDP to FDI. The functional connectivity pattern related to different movements can be promising in future applications as an assessment of post stroke subjects and human machine interface for rehabilitation purposes.

Alveolar recruitment maneuver is usually applied as part of the treatment of acute respiratory distress syndrome, consisting of a transitory and controlled increase in mechanical ventilator pressure delivered to the patient in order to promote opening of collapsed alveoli. Knowing alveolar recruitment potential may help prevent overdistention during alveolar recruitment maneuver. In this work, a method to estimate alveolar recruitment potential based on an exponential model of pulmonary pressure-volume curves using electrical impedance tomography is presented in order to determine if this model is adequate to describe both healthy and injured lungs. Least mean square adjustment is used to estimate total lung capacity based on an exponential model of pulmonary pressure-volume curves. Experimental data from swine was used to develop the method. The results show that the use of an exponential model for pulmonary pressure-volume curve is adequate to describe healthy lungs and may provide information regarding proximity of the overdistention region, but it is not adequate to describe injured lungs appropriately.

The forced oscillation technique (FOT) is a noninvasive method to assess respiratory mechanics. The most widely used commercial ventilator in rodents based on FOT (flexiVent, SCIREQ, Canada) applies a 3-s broadband volume disturbance to estimate the impedance of respiratory entry. The constant phase model (CPM) is adjusted to the impedance of respiratory entry, estimating physiologically significant parameters related to conservative and dissipative properties. Volume disturbance is the overlap of two 2-s epochs (0–2 s and 1–3 s) with a 1-s overlap, improving input estimation respiratory impedance. In this work, the CPM parameters of the small animal ventilator were compared to assess the similarity with the CPM parameters of the calculated signal stretches and whether the parameters of one of these stretches can be used in place of those generated by the ventilator. Respiratory mechanics was evaluated in eleven senescence-accelerated mice (SAMR1) under the administration of methacholine (MCh) by continuous infusion. The impedance of respiratory entry was calculated from three volume disturbances (0–2 s, 1–3 s and 0–3 s). The aim of this work was to evaluate if there are statistical differences between the parameters of the CPM of the sections of 0–2 and 1–3 s compared with that of 0–3 s. The results suggest a similarity between the parameters for increasing doses of MCH and the dissipative parameters for all three signals, while the conservative parameters tends to remain constant until the last but one dose. The plateau analysis showed statistical differences between the doses, while in the ways of adjusting the signals to the CPM they did not present statistical differences ( $$p < 0.0001$$ p < 0.0001 ). In conclusion, we were able to verify that a 2-s period that forms the three-second broadband signal is capable of providing CPM parameters without losing a significant amount of physiological information from the animal.

Peanut oil is widely used in the health care as a carrier for active substances, mainly in topical applications, but its use can pose risks to individuals allergic to the grain. Since ozone and ultrasound are two tools with the potential to cause changes in the molecular structure of the oil, this work aims to evaluate through Raman spectroscopy molecular changes in peanut oil submitted to ozonation and ultrasound. The principal component analysis (PCA) showed changes in the Raman spectra, mainly degradation of the bonds of the methyl and methylene groups and creation of carbon double bonds, and formation of ozonides. Such changes may reduce the allergenic effect of peanuts and contribute to the use of peanut oil in new therapeutic applications.

The electrocardiogram is a great resource for diagnosis in humans and animals alike, as well as an important tool in translational medicine and biology. To better explore signal processing advances on small animals’ ECG, this paper compares linear and nonlinear Haar Wavelet Transform performance on R-peak detection as compared to traditional threshold-based algorithms. Original dog, rabbit and mice records were obtained from PhysioZoo platform, as well as the standard ECG processing algorithm. Algorithms performances were compared on mean and maximum position errors on R-peak detection. All wavelet processing algorithms were written in Python. Nonlinear Haar WT mean error figures were 10 times lower than its linear counterpart for mice and almost 100 times lower for dogs and rabbits. The nonlinear Haar WT also outperformed linear Haar WT on the maximum error indicator, but on the same order of magnitude. We suggest that the PhysioZoo platform should be further explored to advance translational medicine in cardiology by equalizing signal processing techniques application among electrocardiographic records of human and small animals alike.

Currently, diagnostics in the medical field are being automated. Thus, reducing errors of interpretation in diagnoses. This article proposes a recognition method to identify premature ventricular contraction in real time, soon enabling the minimization of damages resulting from arrhythmia. The proposed method consists of two main modules: data extraction module by way of Recursive Least Squares (RLS), guaranteeing data extraction in real time, and the classification module, its inputs being the parameters from the RLS algorithm. In the resource extraction module, autoregressive modeling (AR) is used to extract characteristics. In the classifier module, Support Vector Machine and Multilayer Perceptron are examined. The classifiers’ performance was assessed by standard metrics. The proposed algorithm showed high precision and few false negatives.

Pendelluft corresponds to the air flow from a nondependent lung region to a dependent one. Its occurrence during spontaneous breathing in mechanical ventilation is hard to detect in clinical routines and can lead to injuries. The aim of this study was to develop an automated methodology to diagnose Pendelluft from 2D + time Electrical Impedance Tomography sequences. Our images were acquired using an electrical impedance tomograph (1800 Enlight, Timpel, São Paulo, Brasil) from a normal pig (N) and a pig with the condition (P). Image analysis was performed in Matlab, divided into the following stages: (i) creation of motion vector field (MVF) using Horn and Schunck optical flow; (ii) decomposition of the MVF into a curl-free and divergence-free scalar potentials, D and R respectively, using the Discrete Helmholtz-Hodge Decomposition; (iii) the location of extrema in D and R were tracked over the image sequences N and P, and frequency maps created for the right and left lungs. The degree of similarity of these maps was represented by a parameter $$\phi $$ ϕ . The values of $$\phi $$ ϕ for P were zero for both lungs in the R and D analysis. In the D field analysis, pig N showed $$\phi $$ ϕ values of 6031 and 5407 for respective right and left lungs. The same analysis in the R field gave us a value of 4836 and 4538 for right and left lungs. These results show that our methodology is a possible candidate for automatic detection of Pendelluft, but studies from a large number of human subjects would be needed.

Epilepsy diagnosis depends on the evaluation of long-term electroencephalogram (EEG) recordings performed by trained professionals, turning it in a time-consuming process that is not readily available for most patients. Furthermore, raw EEG recordings are inherently noisy, which makes EEG analysis troublesome. Thus, the present work proposes a methodology for automatic EEG classification of epileptic subjects which uses raw short-duration EEG recordings obtained with the patient at rest. The system is based on machine learning algorithms that use an attribute extracted from the power spectral density of EEG signals. This attribute is an estimate of functional connectivity between EEG channel pairs and is called debiased weighted phase-lag index (dWPLI). The classification algorithms we used were support vector machines (SVM) and artificial neural network (ANN). EEG signals were acquired during the interictal state, i.e., between seizures, and had no epileptiform activity. Both raw and pre-processed recordings of 15 epileptic patients and 10 healthy subjects were used to evaluate the method’s performance. The algorithms reached their maximum classification performances, 100% accuracy, using input attributes extracted from raw data. The results show the feasibility of the proposed system, given its high classification performance.

This paper presents a study about transfer learning using convolutional neural networks for detecting breast cancer in histopathological images. Transfer learning is a deep learning technique that reuses pre-trained neural network models to perform a particular task, which in this paper is to detect breast cancer in the referred images. Three convolutional architectures were tested: ResNet-18, ResNet-152, and GoogLeNet. The architectures were implemented in Python using PyTorch and trained using GPUs in the Google Colaboratory environment. Moreover, a random image processing stage was used to avoid overfitting, as well. Results indicate that ResNet-152 presents the best results reaching a mean accuracy of 84%, a precision of 90%, and F1 Score of 88%.

In recent years there has been considerable advances in the development of assistive technologies to enable the Person with Disabilities (PwD) better participate in society and interact. One way to allow PwD interaction is using interfaces based on the electrical potentials that our body presents, called biopotentials. The acquisition and the classification of these are crucial steps in the development of these technologies. In this work, a setup to acquire electrooculogram (EOG) signals was developed to track eye movements for a minimally invasive computer/game interface. This work includes setup and creation of a dataset, feature extraction of the collected signals and the implementation of classification algorithms. Three machine learning algorithms were designed to classify the EOG signals based on its characteristics: Softmax Regression, Gaussian Discriminant Analysis (GDA) and K-Nearest Neighbors (KNN). Comparing the algorithms classification performances, KNN presented the best results with 88.9% overall accuracy.

This study presents principal component analysis (PCA) intra-subject variability of lower limb surface electromyography (sEMG) at different muscle stretch-shortening cycle (SSC). Several key steps are presented on the research of muscle force production for human in-vivo and noninvasive studies as well as on SSC contribution at gait, run, and jump with the need for separation of muscle and tendon behavior. Complexity and unpredicted multiple muscle actuation are highlighted with the need for extraction of PCA components from muscle stretch-shortening cycle sEMG, namely on lower limb stereotyped muscle patterns assessed on standard maximum vertical jump (MVJ). The purpose of this study is to apply PCA to sEMG linear envelopes of lower limb selected muscles at different MVJ, to detect lower number of components explaining maximum sEMG variability, representative of low dimensional signal control on muscles synergies. Different MVJ were assessed with subject specific PCA of lower limb sEMG during Counter Movement Jump (CMJ), Drop Jump (DJ), and Squat Jump (SJ). Intra-subject variability of sEMG PCA allowed the detection of two components explaining maximum variability with different profiles and muscle grouping at CMJ, DJ, and SJ. First component (PC1), representing larger signal variability, presented higher value at SJ and DJ than CMJ, with the need for a higher number of PC’s to explain the same cumulative percentual variance at CMJ than DJ and SJ. Comparison with intra-subject linear (r) and cross-correlation (CCr) presented higher r and CCr at SJ and DJ than CMJ, with higher paired correlations at the muscles grouped on the same component. Comparison of intra-subject analysis with previous study on same subject single trial allowed subject-specific generalization of the preceding results.

The purpose of this study was to evaluate how skull density behaves after decompressive craniectomy (DC) through Hounsfield Unit (HU) quantification (Hounsfield in J Comput Assist Tomogr 4(5):665–674 [1]). The margins of the bones of the frontal and occipital regions adjacent to the decompressive craniectomy and the opposite regions without surgery in the early and late stages were analyzed. In the immediate postoperative period, higher bone density values were found at the margin without craniectomy in the frontal bone (12.5–32.28%) and this difference decreased in the late phase (0.53–15.74%) and in the occipital bone. The maximum density values were higher at the margin of the decompressive craniectomy in both the early and late stages. These informations can help the neurosurgeon about changes in the bone quality of the skull following the surgery.

Computed tomography (CT) and positron emission tomography (PET) allow many types of diagnoses and medical analyses to be performed, as well as patient monitoring in different treatment scenarios. Therefore, they are among the most important medical imaging modalities, both in clinical applications and in scientific research. However, both methods lead to radiation exposure, associated to the X-rays, used in the CT case, and to the chemical contrast that inserts a radioactive isotope into the patient’s body, in the PET case. It is possible to reduce the amount of radiation needed to attain a specified quality in these imaging techniques by using compressive sensing (CS), which reduces the number of measurements required for signal and image reconstruction, compared to standard approaches such as filtered backprojection. In this paper, we propose and evaluate a new method for the reconstruction of CT and PET images based on CS with prefiltering in the frequency domain. We start by estimating frequency-domain measurements based on the acquired sinograms. Next, we perform a prefiltering in the frequency domain to favor the sparsity required by CS and improve the reconstruction of filtered versions of the image. Based on the reconstructed filtered images, a final composition stage leads to the complete image using the spectral information from the individual filtered versions. We compared the proposed method to the standard filtered backprojection technique, commonly used in CT and PET. The results suggest that the proposed method can lead to images with significantly higher signal-to-error ratios for a specified number of measurements, both for CT (p = 8.8324e-05) and PET (p = 4.7377e-09).

In this paper, it is proposed an arterial pressure signal estimation technique from electrocardiographic signals. The study also covers, fundamentally, applying knowledge from the biomedical engineering field, in analysis and signal processing of biomedical signals, because it makes use of digital filters, correlation, covariance and other methods of signal treatment, using developing tools to assist medical diagnostics. The implemented method is based on the Kalman filter’s use, which was designed considering a system model obtained from invasive arterial pressure measurements to allow the development of a non-invasive technique. Obtained results granted the estimation of the systolic and diastolic pressures, to ensure this fact, the study took into account the analysis of the system’s performance by evaluating the quantitative mean of the estimation error, the RMSE index.

Microvolt T-wave Alternans (MTWA) is considered an early marker for subjects with high risk sudden cardiac death. Classical MTWA quantification (CM) requires accurate T-wave peak detection risk mark and approaches based on morphological T-wave analysis have been proved to be effective, such as Hilbert Transform approach (HT). This work proposes the hypothesis that accurate T-wave detection may lead to improvements on MTWA quantization. Three distinct methods were testes for T-wave identification: fixed-window approach, adjustable-window, and triangle area approach. These methods were applied on ECG signals from Physionet T-wave Alternans database. The results are compared using linear correlation and area above ROC curves. Also, the results were evaluated by positive predictive value (PPV) and the negative predictive value (NPV), sensitivity, specificity and accuracy. Results showed high dependency between HT and T-wave detection methods and the results variate as the detection method changes. The results indicate that CM, as expected, is not T-wave detection dependent and obtained statistical similar results for the three approaches.

Schizophrenia is a mental disease with a great number of clinical manifestations that makes diagnosis a great challenge. Until a correct diagnosis is attained, the patient experiments mental suffering that can lead to social conflicts, involuntary accidents, and suicides. Early diagnosis, despite the clinical complexity, is therefore of utmost importance, and several recent studies focus on analyzing structural brain modifications that have been correlated to schizophrenia, and that can be detected in anatomical magnetic resonance images. Previous research applying machine learning to such images presented promising results. However, the scope was limited to analyzing only one or few slices of the brain while not using recent algorithms at the core of the classifiers. This can lead to information loss due to sub-optimal features extraction. In this study we created machine learning models based on Convolutional Neural Networks, and evaluated the best training parameters based on a data set of magnetic resonance images from persons with schizophrenia and from a control group. We analyzed the performance of the classifiers, first trained with individual slices of the brain and later with different combinations of multiple magnetic resonance slices. Our results suggest that it is possible to increase the performance metrics such as accuracy, sensibility, and precision of a classifier from approximately 50% when trained with a single slice, to over 80% when trained with a properly selected combination of slices.

Lung ultrasonography (LUS) is a recent evaluation method for many thoracic diseases. Thoracic acoustic mismatch produces some artifact patterns in the ultrasound B-mode imaging that can be related to specific types of lung diseases. In this study, a simulation method of a LUS phantom was proposed to evaluate artifacts origins. Five configurations of LUS phantom were implemented using the k-wave MATLAB toolbox. The first simulation aimed to achieve A-lines images and the others aimed to achieve B-lines images. A-lines could be seen as reverberation artifacts and B-line as an artifact probably originated by an acoustic trap for the signal.

Facial expressions are considered as a universal language method with non-verbal communication between humans. The surface Electromyography (sEMG) is a technique to acquire and processing signals obtained from the electrical activity of the contraction of voluntary muscles. From that, this work presents a preliminary study of recognition of facial expression obtained from sEMG signals. Signals from 4 subjects were acquired for six basic facial expressions that expresses the following emotions: happiness, surprise, sadness, angry, disgust, and fear. The sEMG signals were acquired from two muscles: zygomaticus major and corrugator of the eyebrow. Three feature sets for sEMG and four different classifiers were evaluated. The best combination was found with the TD9 feature set and SVM with radial basis function kernel classifier, reaching 79.8% of accuracy. Among the expressions, the best recognition was happiness, with individual accuracy of 99.2%. The most difficult expression to classify was the expression of disgust.

This paper presents a method that uses a sequential representation to train Hidden Markov Models as an algorithm for the supervised morphological classification of erythrocytes in peripheral blood samples from patients with sickle cell anemia, considering three classes: circular, elongated and with others deformations. This sequential learning method provides the probability of belonging the object to the class and for the representation of the red cell contour, characteristics are not obtained, but the contour is analyzed as a sequence of curvatures. The experimentation carried out analyzes each group as a class and considers 3, 8, 9, 10 and 11 states, so that the method is capable of dealing with the local angular differences existing in this representation, with the aim of improving the performance of the classification obtained so far. To check the effectiveness of this method, we use samples with balanced classes formed by images of individual erythrocytes, in similar amounts for each of the three classes. Measurements of sensitivity, precision, specificity, F1 and classification accuracy were obtained. The best results were obtained for the representation considering 10 states.

The heart rate variability (HRV) is the difference between consecutive R-R intervals of heartbeats measured in milliseconds. HRV indices represent the role of sympathetic and parasympathetic autonomic branches. Even though HRV is considered an indirect biomarker of Autonomic Nervous System, there are not yet standardized protocols providing reliable clinical measures. One of the reasons is because HRV techniques requires long recording periods. There are attempts of decreasing the required recording, such as the strategy of ultra-short HVR recording (<one minute), which could make the utilization of the technique easier. However, there is little published about its reliability. This work proposes a method to evaluate the reliability of ultra-short HVR based in Poincare map and Recurrence Quantification Analysis, well known methods to assess nonlinear and dynamic information from a system, in order to verify the reliability of the use of ultra-short term HRV. Then, these results was compared with the classical HRV coefficients, such as rMSSD, recorded from subjects in spontaneous breathing and also, in controlled breathing protocols. As a conclusion, using the proposed methods, we were able to show the discrepancy between the segments of interest, both on mean and in variance, explained in the analysis of main components.

Cost management in healthcare organizations plays a strategic role in creating value for the patient. In this scenario, medicines represent a significant portion of costs in health organizations, so their internal logistics should work in the best possible way. A strategy to achieve such efficiency is the unidose process. The present study aims to evaluate the financial feasibility of the unidose process automation in a public hospital. The main costs and savings due to the automation were listed and to assess the financial statement the simple payback and discounted payback were used. Through the simple payback result, the financial return would occur in 5.06 years, while the discounted payback pointed a financial return in 5.71 years. Though the initial investment, automation decreases overall costs and turns more concise the productivity, thus improving efficiency to the process.

The infrastructure and the technology park in Primary Health Care (PHC) have become more complex and more required in recent years due to population growth. One of the managers’ concerns in healthcare establishments is the provision of quality health services and patient safety. Therefore, the actions of Clinical Engineering (CE) are essential support, especially with decentralized management models through Ubiquitous Health Technology Management and with the management and quality control tools that have been proved to be efficient in CE when assisting the management of the technology parks. This article presents the results of a study that used data obtained from the Healthcare Failure Mode and Effect Analysis (HFMEA) to identify monitoring parameters in Ubiquitous Technology Management of a municipal health department PHC in the state of Santa Catarina. The CE team identified the dental air compressor as a priority, due to its importance in dental care based on data from the information system (IS) used in the technological park management. The HFMEA development team extracted the failure modes from 172 work orders in the IS. Five failures, representing more than 80% of the total, were chosen. Then, a system for remote monitoring was implemented in the Health Technology Ubiquitous Management model to remotely monitor the compressors and track their parameters indicated by the HFMEA. As a result, it was possible to perform scheduled maintenance in the intervals of patients’ appointments, without the need for cancellation, thereby reducing unscheduled stops, adding quality to the technological process, and increasing the reliability and safety of the health service system. This study should always be fed back with new indicators for the system to become even more robust, reliable, and updated.

The application of usability techniques in health care establishments has the potential to identify, analyze and implement improvements to reduce adverse events and increase patient safety and reliability in technological health processes. Due to the increase in technologies in health care establishments and its use in the prevention, diagnosis and treatment of various diseases, the Health Technology Management process consists of an extremely effective approach to clinical engineering. A rapid review of the usability techniques application in medical equipment was performed to look for the evidence available in the literature and thereby contribute to developers, manufacturers, health professionals, technology managers and other actors in the technological process of applying usability concepts in medical equipment. The research was performed through searches in scientific databases. A total of 31 studies were selected in which various usability techniques were applied, the most frequent being questionnaires and usability tests. The medical equipment in which they were most studied were infusion pumps, pulmonary ventilator and defibrillator. With this research it was possible to present main studies current panorama and to show the importance of applying usability techniques in medical equipment, to demonstrate the relevance of bringing the clinical and technical area closer in the processes involving health technologies, in addition to discuss the main ones considerations of the implementations of the techniques in order to reduce the risks of using the technologies in the health units and thereby improve patient safety.

Parkinson’s Disease (PD) is associated with the loss of dopaminergic neurons in the substantia nigra causing classic motor symptoms such as bradykinesia, resting tremor and stiffness, in addition to non-motor symptoms such as respiratory disorders. The aim of this paper is to improve our knowledge about the pathophysiological changes in the respiratory system of individuals with PD, in different degrees of disease using respiratory oscillometry. The results obtained in never-smoking 30 patients with PD (12 level 0–1.5 and 18 level 2–3) were compared with 20 controls. There was a significant decrease in mean reactance Xm (ANOVA p = 0.008), significant increase in resonance frequency (ANOVA p < 0.0001) and reactance area (ANOVA p = 0.045). There was no significant difference in mean and total resistance in the 0–1.5 and 2–3 groups compared to the control group. Peripheral resistance, in contrast, were increased in these groups (p < 0.05). The resonance frequency was also higher in in the 0–1.5 and 2–3 groups compared to the control group (p < 0.05). The results are consistent with the pathophysiology of PD. Respiratory oscillometry contributes to improving our knowledge about the changes that occur during the worsening of the disease. In addition, the analyses carried out indicate that this method has great potential for application in the functional evaluation of patients with PD in the initial stages of the disease.

This paper presents the process of using remote analysis of primary health care technology conditions through machine learning algorithms to assist the decision-making processes of ubiquitous management in clinical engineering. It includes data collection, analysis, and exhibition. This method was applied to dental technology in primary health care, a dental air compressor. The model was developed in the Microsoft Azure Machine Learning Studio platform testing the algorithms of neural networks, logistic regression, decision jungle, and decision forest, which, after comparison, was the most suitable algorithm for the purpose. The data was transformed to comprehend the influence of time in the read values to obtain an efficient result in the platform. The code execution and the exhibition of the classification results were made using a web-service and Python scripts. As a result, the system presents real-time notification and identification of health technology failures, supporting management solutions in clinical engineering.

This work consists of a literature review that aims to evaluate the effects and efficacy of two drugs used to treat individuals with COVID-19: chloroquine (CQ) and hydroxychloroquine (HCQ). Both drugs have demonstrated antiviral activity against the new coronavirus in in vitro tests. However, there is currently no strong evidence from well-designed controlled studies of COVID-19 therapies tested in humans. In addition, the evidence on the effects of drugs on patients is extremely limited. The search for evidence was made from five chosen databases, and after applying the criteria for inclusion and exclusion of articles, 5 publications were obtained, which represented the basis for the construction of this work. We concluded that, in relation to CQ, no favorable outcomes were found in relation to its use. High doses of this drug can increase lethality due to the prolongation of the QT interval, and lower doses could not estimate evident benefits in infected patients. Assessing the results of HCQ, it can be concluded that more studies are needed to effectively use this drug in the treatment of individuals with COVID-19.

Urgent and emergency care, generally, has a demand greater than the availability of health services. In this context, given the high demand of High-Risk Pregnant Women, and other women users, for urgent and emergency obstetric services available in Tocogynecology Emergency Service (TES), it is possible that patients will not be attended to in the expected time. This research aims to analyze data from the Embracement with Risk Classification (EWRC) of a TES of the year 2018. For this purpose, the relationship between EWRC and errors in TES records was investigated; the of errors in general and patients’ waiting time for Medical Assistance (MA) in TES; the monthly average of receptions by risk classification and specialty of MA; the patient's lead time between the EWRC and the MA; and the rate of patients with waiting time for MA higher than that established for clinical priority. From the analysis, it was observed that, as the patient's clinical priority increases, there is a tendency that this user will not be attended by the medical team within the expected time.

Good health technology management (HTM) is mandatory to assure high quality of the service delivered by any healthcare-providing institution (HCI). When fast responses are needed on critical aspects of the institution´s installed equipment park, as during the current coronavirus disease pandemic, a computerized HTM system is considerably valuable. This article presents typical questions that can be responded within a few seconds using GETS, a HTM system developed at UNICAMP to support clinical engineers at Brazilian public HCI. Using data from 10 public HCI registered in the GETS system (888 pulmonary ventilators), it was possible to see, for instance that, only ~28% of the ventilators are aged less than 5 years, while ~45% are 11 year-old or older, which is a cause for concern because we have previously observed that equipment downtime due to corrective maintenance, as well as failure frequency and maintenance cost, increase with age. This piece of information is certainly helpful to quickly evaluate priorities for equipment purchase and distribution, and to support long-term planning of equipment acquisition, as to allow better preparedness for (unavoidable) public health crises and more rational use of financial resources by the public health system.

Equitable supply of life-sustaining equipment (LSE) is an important guide for assessing public health service provision. However, the inadequate geospatial distribution of this equipment can pose a difficulty in accessing it. In this attempt, the objective of this study was to analyze the geospatial distribution of life maintenance equipment in the Brazilian national territory using a database from the Department of Information Technology of SUS, analyzing its availability, access at the municipal level as well as its correlation to regional income per capita. This cross-sectional, descriptive study with a quantitative approach used spatial analysis tools to determine the existence of Global Spatial Autocorrelation (Moran's I) and Local Spatial Autocorrelation Index. Thus, it was observed that the highest rate of equipment is concentrated in the Southeast region with 52.9%, followed by the Northeast region 18.2%, South region 15.5%, Midwest region 8.5% and the North region with 4.9%, which can be justified by the regional GDP. It is possible to observe a directly proportional relation between the GDP value of the states and their amount of equipment. We conclude that the distribution of LSE was greater in the Southeast, Northeast and South regions, thus showing an imbalance in the North and Northeast regions. There was also a need to implement public policy incentives to promote improvements, reducing the difficulty for the population to have access to this equipment.

Diagnostic imaging equipment is important for assistance in the Unified Health System, however, the lack of adequate geographical distribution of these equipment can hamper access to services. The objective was to analyze the geospatial distribution by data from the SUS Information Technology Department of equipment, as well as the availability and access to this equipment in the national territory and its relationship with the states’ per capita income. A cross-sectional study using spatial analysis tools to determine the existence of Global Spatial Autocorrelation (Moran's I) and Local Spatial Autocorrelation Index. The highest rates are concentrated in the Southeast, South, and Midwest regions, and the lowest are in the North and Northeast regions, which can be justified by the local GDP. Therefore, there is a lack of adequate distribution and management of imaging equipment, especially in the poorest regions. It shows the population’s difficulty of access and the need to implement public policies focusing on access to these equipment.

The current health crisis caused by the new coronavirus (SARS-CoV-2) has created a great demand to widely explore the mechanisms of mechanical ventilation for life support in Intensive Care Unit (ICU). This work describes the basic concepts of the mechanical ventilation process and a brief technical description of both invasive and non-invasive ventilator. Additionally, describes the importance of this therapy as it is the main mechanism for assisting patients in a critical state of coronavirus disease (COVID-19). It also presents approaches that have been considered to meet the current demands and prevent the collapse of the health system. Finally, it presents the responsibilities of clinical engineers in this scenario.

Medical equipment is used in the diagnostic, monitoring and therapy, offering numerous benefits to the patients. However, these devices’ technical factors and the human aspects can produce adverse events, which may cause severe consequences for the patients. Therefore, it is crucial to provide means to mitigate these situations by improving safety in equipment use. Thereby, our objectives are to present to the scientific community the main alerts, dangers and failures related to medical equipment use and ways to attenuate them. For that purpose, we performed an analysis of adverse events reported for some medical equipment in the Food Drugs Administration (FDA/USA) and the Brazilian Health Surveillance Agency (ANVISA) databases, since 2016. Finally, we classified the events into different categories, according to similarity. The results show a total of 3100 cases registered in the FDA for the equipment at the study and 75 cases in ANVISA for two of this equipment. Based on the list of the top ten health hazards (2016–2020) provided by the Emergency Care Research Institute (ECRI) we were able to understand which equipment most offer hazards and the main ways to mitigate them. Overall, we found that the risks are common to medical devices, so the best way to deal with adverse events is prevention, through good maintenance and medical staff training for dealing with them.

This paper presents the process of quality assessment of emergency corrective maintenance of critical care ventilators in a node, IPT-POLI, of a voluntary network, the initiative + Maintenance of Ventilators, led by SENAI-CIMATEC to perform maintenance on unused mechanical ventilators during the context of the COVID-19 pandemic in Brazil. A procedure was developed for quality assessment of equipment subjected to corrective emergency maintenance, covering the main points of three main standards for performance and safety assessment. A set of seven critical care ventilators was evaluated according to the following parameters: leakage current, resistance of protective earth, accuracy of control and instruments, delivered oxygen test, and alarms. All evaluated ventilators were out of use for more than 2 years and underwent corrective emergency maintenance before having their performance and safety assessment. In electrical safety tests, all equipment presented values prescribed for the standard. In the assessment of ventilator parameters, all equipment did not perform sufficiently according to the standard. It was possible to conclude that the choice of criteria to perform the quality assessment in critical care ventilators proved to be important and can be a report of great value for future pandemic scenarios such as that experienced during the COVID-19 pandemic.

Early detection of breast cancer is a critical part of the strategy to improve diagnosis and reduce the mortality caused by this disease. Benefits and damages of screening tests have been discussed in recent years. Those discussions, along the limitations of mammography and its unavailability to our medical centers, made us evaluate the accuracy of thermography on detecting breast abnormalities. Advances in thermography technology associated with tools for improving image analysis have shown positive results so they could become a reliable tool. The objectives of this research were to verify the thermal behavior malignant or non-malignant tumor, and to compare the sensitivity and specificity of mammography imaging exams (MMG), besides the infrared thermography (TMG). There were 25 volunteers involved in the study, who performed both tests mentioned above and the biopsy (gold standard for breast cancer diagnosis). A dynamic protocol was performed with the application of skin cooling method as the images were analyzed after eight minutes of reheating. The participants are on average 49.5 years old and 72% had dense breasts. The temperatures in the tumoral regions and the thermal densities was higher in malignant tumors than benign tumors. The sensitivity and specificity for mammography were 73% and 70%, respectively and, for thermography, 83% and 74%, respectively. The results of this study show that thermography has the potential to be used as an aid to mammography in the early diagnosis of breast cancer.

In December 2019, the World Health Organization (WHO) was alerted to an increase in cases of pneumonia in the city of Wuhan in China, confirming that it was a respiratory infection caused by a new strain of coronavirus, previously unknown in humans. COVID-19, a disease caused by the coronavirus-SARS-CoV2, was declared pandemic by the WHO in March 2020, due to its rapid worldwide spread. The form of transmission of the disease occurs through droplets disseminated in the air, orally-fecally or by fomites. Studies show that the nosocomial spread of the virus may be responsible for the increase in the number of cases in some countries, which makes the use of individual protection equipment the measure of greater control of nosocomial infection. However, the increase in the consumption of these inputs in an indiscriminate manner can cause an unsustainable financial impact for hospital institutions. The purpose of this study is to show the partial results of the analysis of the costs of Personal Protective Equipment (PPE) in a philanthropic hospital in the inland city of Bahia, after the beginning of the COVID-19 Pandemic. The results drew attention to the 33.13% increase in the hospital cost with personal protective equipment in the first quarter of 2020, which raises a concern regarding the institution's financial difficulty in maintaining the supply of these supplies.

Minimally invasive surgical procedures are in evidence and are, therefore, the major worldwide trend. They correspond to a great technological advance that aims to promote patient safety, minimizing complications and making possible some complex surgeries that were not possible to be performed in the past. Highly complex surgeries require the use of equipment that presents high precision in cutting biological tissues and that is also combined with cauterization, thus avoiding complications caused by hemorrhages and even infections. The objective of this work was to evaluate the power/intensity generated by ultrasonic shears used in surgical procedures. Twenty-five Harmonic Ace® shears—HAR36 were evaluated, with four handpieces coupled to eight different ETHICON GEN11 generators. The generators were configured to generate the Level 5 power, standard for cutting, Level 3, standard for coagulation and Level 1, also used for coagulation with greater efficiency. For each GEN11 configuration, the maximum generated power values were measured using an Ohmic Instruments UPM-DT-1 Ultrasound Power Meter. The expected value and standard deviations were calculated using EXCEL (Microsoft Corp.). The average powers generated for all evaluated devices were 1.08 ± 0.80 W for Level 1, 3.74 ± 2.28 W for Level 3 and 9.18 ± 3.32 W for Level 5. It was found that there is a 20-fold variation between the lowest and the highest power generated, showing the importance of implementing an adequate quality control protocol for these devices. It was also found that, even during the standard test of equipment, high levels of intensity are generated that can subject operators to risks if they do not take proper care, requiring adequate training of these professionals. Thus, to avoid risks to operators, this work suggests a safety protocol with the steps to be followed when activating the ultrasonic shears.

Variability in the force production is known to be influenced by intrinsic and extrinsic properties of the neuromuscular system. Here, we aim at investigating the role of visual feedback (presence or absence) on the neural control of muscle force during a broad range of isometric contractions of a hand’s muscle. Eight participants performed isometric abductions of the index finger in six submaximal contraction intensities (5–75% of the maximum voluntary contraction, MVC). In each trial, participants performed the task with and without visual feedback of the performed force. High-density surface electromyogram (EMG) was recorded from the first dorsal interosseous muscle. Spike trains of motor units were obtained after semi-automatic decomposition of surface EMG signals. The interspike intervals (ISI) of motor units and the effective neural drive to the muscle (smoothed cumulative spike train, sCST) were estimated. The mean value, standard deviation (SD) and coefficient of variation (CoV) were computed for the force, sCST, and ISI. No interaction between visual feedback and contraction conditions were found, neither an effect of visual feedback on the dependent variables. An increase in the contraction intensity was followed by an increase in the mean sCST and a decrease in the mean ISI. Contraction intensity increased the force SD and the sCST SD. CoV of force and sCST both only decreased from 5%MVC to 30%MVC. On the other hand, contraction intensity did not change ISI SD, but increased ISI CoV. These results revealed that visual feedback did not influence motor control strategies in a large range of force levels. Moreover, we provided evidence that force variability is mostly influenced by fluctuations in the activity of a population of motor units rather than the discharge properties of individual motor units.

Epilepsy is a chronic brain disorder characterized by recurrent seizures due to abnormally synchronized electrical discharges. Neurofeedback (NFB) is an operative conditioning technique used to reinforce or inhibit specific frequencies of electroencephalogram (EEG) activity. Augmentation of the sensorimotor rhythm (SMR) is a common neurofeedback protocol for epilepsy patients. In the present work, we aim to evaluate the espectral outcomes of a neurofeedback protocol based on SMR augmentation in refractory epilepsy patients. The participants underwent five sessions of NFB while having their EEG recorded with a 22-electrode system. The sensorimotor rhythm (SMR) before and after the NFB training differed significantly in the frontal, central electrodes, and in the channel used for training. Our results demonstrate that NFB training can improve regulation of SMR in these patients.

Gelotophobia is the pathological fear of being ridiculed and is considered a symptom of a social anxiety disorder (SDA). Gelotophobia can negatively interfere with academic activities, which requires public exposure in various situations. In this article, we present an exploratory analysis of the prevalence of gelotophobia in a sample of undergraduate and graduate students. The results reveal that gelotophobia is highly prevalent in the sample, with great potential to influence their academic performance negatively. The present study is the first step to help university students to overcome the academic obstacles interposed by social anxiety.

Bipolar disorder (BD) is characterized by mood swings that have been associated with a cyclic dopaminergic dysregulation, with hyperdopaminergic states being related to manic symptoms. To date, however, little is known about how such imbalance alters the functioning of brain regions within the dopaminergic mesocorticolimbic (MCL) circuit. In this study, we characterize the changes in oscillatory power in MCL regions associated with a hyperdopaminergic state induced by a single administration of GBR 12909, a highly selective dopamine transporter inhibitor. To do that, we recorded local field potentials across the prelimbic cortex, nucleus accumbens, ventral hippocampus, basolateral amygdala, and ventral tegmental area of mice following the administration of GBR12909 or saline. We found that GBR 12909 administration induced significant changes in the power spectrum density in prelimbic cortex, nucleus accumbens and ventral hippocampus, indicating that elevated levels of dopamine alter the activity of key regions of the MCL circuit. Future studies are necessary to establish the relationship between these alterations and the mania-like behaviors observed in hyperdopaminergic states.

Autism spectrum disorder is characterized by being difficult to diagnose due to limited knowledge of its etiology and pathophysiology. There are, however, biomarkers that correlate to a limited extent the presence of the disorder, as well as its severity. A fuzzy inference system that simultaneously aggregates multiple biomarkers for assisting in the assessment of the autism spectrum disorder is proposed in this work. When combining the different biomarkers, the fuzzy decision support system is suitable to be applied in identifying the presence and the severity of the autism spectrum disorder. The Mamdani fuzzy model is employed to relate the input variables oxytocin, serotonin, and vitamin D levels to obtain an autism scale as the outcome. The assessment of autism spectrum disorder is given in the form of stratification (classes) and their respective score (score). The proposed system is consistent with the scientific literature, detaching a greater influence of serotonin on the onset of ASD and its severity. Moreover, the fuzzy assessment detaches that when the level of the vitamin D is reduced, there is a worsen on the onset and the severity of the autism spectrum disorder.

Parkinson’s Disease (PD) is a neurodegenerative progressive disorder characterized by asymmetric lateral motor impairment, usually associated with key clinical motor symptoms, such as tremor, rigidity and bradykinesia. Although it is known that specific local field potentials (LFP) band power recorded from the subthalamic nucleus (STN) correlate with some of these symptoms, there is little evidence about how both STN hemispheres information could be used to predict the patient’s clinical condition, and, possibly, used for optimizing the current deep brain stimulation protocols, since identical bilateral stimulation can lead to worsening symptoms. Bearing these ideas in mind, this work proposes a multivariable linear regression approach for patients’ motor symptoms’ prediction based on classical LFP band power (theta (4–8 Hz), alpha (8–13 Hz), beta 1 (13–22 Hz), beta 2 (22–35 Hz), gamma 1 (35–100 Hz), gamma 2 (100–150 Hz), gamma 3 (150–200 Hz)) extracted from contralateral and ipsilateral STN recordings, which aims to identify possible interhemispheric electrophysiological correlates of clinical symptoms. Besides, another prediction scenario is presented aiming to verify if there are any LFP frequency bands that could explain asymmetric clinical manifestation. As a major result, we observed that alpha and beta 2 relate to rigidity and beta 2 to bradykinesia when using only contralateral data. When combining both hemispheres, it is seen that gamma 2 is associated with tremor and beta 1, beta 2 and gamma 1 with bradykinesia. Also, adding ipsilateral data could lead to worsening prediction performance, except for beta 1 concerning the bradykinesia symptom. At last, it was found that there are frequency bands which could help explaining symptoms’ asymmetry, such as theta for rigidity and alpha for bradykinesia.

Parkinson’s Disease (PD) is a neurodegenerative illness associated with dopaminergic loss in the basal ganglia circuit which can lead to heterogeneous motor symptoms such as tremor, rigidity and bradykinesia. The electrophysiological phenomena underlying these symptoms is not completely understood, which imposes a major challenge for designing customized and more efficient Deep Brain Stimulation (DBS) protocols to match patients’ specificities and needs. Recently, it has been shown that elevated and prolonged beta (13–35 Hz) oscillations (i.e. beta bursts) from the subthalamic nucleus (STN) are associated with motor impairment in PD. Furthermore, motor improvement induced by pharmacological treatment relates to attenuation of intermittent beta activity. This work aims to analyze beta burst dynamics of two phenotypes of PD patients—the tremor dominant (TD) and the postural instability and gait difficulty (PIGD)—to better understand how features of beta oscillations correlate with the motor symptoms in such different PD’s categories. Through a wavelet analysis of 35 LFPs recorded in the sensorimotor portion of the STN from 15 TD and 20 PIGD patients, we show that PIGD patients exhibit longer beta bursts, while TD patients exhibit higher beta burst probability and an inverse significant correlation of burst duration with the rigidity score. These findings may provide critical markers for characterizing the electrophysiological mechanism underlying PD phenotypes and their symptoms, as also contribute to more efficient and customized DBS strategies.

This paper describes the development of a low-cost software, called Rat Steps, which allows the obtention of quantitative data (total distance traveled and average speed) as well as the graphic trajectory performed by an animal in the open field test. This behavioral test is widely used in neuroscience in order to visualize locomotor impairment following acute brain injury, including stroke, as well as the effect of experimental therapies for these neural disorders. The main tools used for the software development were digital image processing techniques, Python programming, OpenCV library and machine learning algorithms, including the Mean Shift method. The software was successfully developed with effective obtention of quantitative parameters from the Open Field Test, which allows several applications in neuroscience research.

Chloride accumulation inside neurons is related to excitability and to the induction and maintenance of epileptiform activity. Studies propose that cation-chloride cotransporters KCC (potassium-chloride cotransporter) and NKCC (sodium–potassium-chloride cotransporter), nonsynaptic mechanisms associated with chloride (Cl−) homeostasis, may be targets for anticonvulsant treatment. However, the contribution of these cotransporters to the neuronal activities during epileptiform discharges is not yet clear. This study aimed to investigate the effect of the cation-Cl− cotransporters (KCC and NKCC) during non-synaptic epileptiform activity (NSEA) through mathematical modeling and computational simulations. The mathematical model represents electrochemical mechanisms of the granular layer of the dentate gyrus in the rat hippocampus, such as ion channels, the Na/K pump, KCC, NKCC, etc. For KCC and NKCC, in particular, ionic fluxes were estimated according to the Michaelis–Menten formalism, considering the reactions of their physiological ligands in an equilibrium state at each instant. Simulating experimental procedures, the results show that the blockage of both cotransporters is not enough to suppress non-synaptic epileptiform discharges after they have been triggered. According to the simulations, KCC and NKCC contribute to intracellular Cl− accumulation and to increase neuronal excitability. However, the Cl− flux through ionic channels is sufficient to maintain the intracellular Cl − concentration at the high level necessary to the occurrence of epileptiform discharges.

Spreading Depression (SD) is a brain phenomenon that involves intense neuronal activities and, consequently, change the energy metabolism responsible for the production of ATP and lactate. The aim of the present work was to investigate, using mathematical modeling and computational simulations, the behavior of ATP and Lactate production during the SD. The mathematical model used to simulate SD wave describes electrochemical mechanisms from the dentate gyrus of rat hippocampus. In this work, a mathematical description of the reactions involved in energy metabolism responsible for the production of ATP and lactate, in neurons and glia, was also used to perform the simulations. Investigating how neuronal and glial energy metabolisms are able to maintain the level of ATP and lactate, it was possible to described how happens the lactate increase in the neuronal tissue during the SD. Simulations suggest that the lactate produced by glial metabolism is essential for neuronal metabolism to maintain the ATP level during SD.

Spinal cord stimulation (SCS) is currently used to treat chronic pain and has been shown to be effective in the treatment of other neurological disorders, such as Parkinson’s disease. The electrodes used for SCS are placed adjacent to the nervous tissue and thus can induce inflammation that may interfere with its efficacy. One of our previous studies showed that acute implantation of spinal cord electrodes resulted in substantial microglial activation throughout the transversal sections of the spinal cord at the region of implant, but data on microglial activation after longer periods is still lacking. To investigate microglial activation in the spinal cord after a chronic period of implantation, 3 wistar rats were implanted with SCS electrodes in the epidural space under thoracic vertebra 4 (T4), while 4 animals underwent a sham surgery. Thirty seven days after the surgery, the animals were perfused and spinal cord sections of the implanted region (T4) and regions close (thoracic levels 3 and 5—T3 and T5) and distant to the implanted tissue (cervical level 4—C4 and lumbar level 1—L1) were analyzed by calcium-binding adaptor protein-1 (IBA-1) immunohistochemistry to determine microglial amount and morphology. There was a greater microglial activation at the implant site (T4) and in nearby regions (T3 and T5) in animals of the electrode group. In addition, at T4, the amount of activated microglia was higher at regions in close contact with the electrode than in regions farther from the electrode, with the highest percentage of activated microglia at the dorsal funiculus (18%). To our knowledge, this is the first study describing the microglial activation following chronic implantation of epidural electrodes, and it provides important new information regarding the spinal cord tissue response to chronic implants.

Intracortical microstimulation (ICMS) is an invasive stimulation technique through which it is possible to excitate and inhibit the activity of neurons from different cortical regions. The ICMS has been used in the context of neural prostheses targeting the restoration of neurological functions and as possible tactile feedback in brain-machine interfaces. Several protocols of microstimulation have been implemented to stimulate the primary somatosensory cortex (S1). The literature describes the direct effects of ICMS upon the activity of neurons in the stimulated area, though the distribution of the neuronal activity and the indirect effects of that stimulation, that is, those that occur far from the stimulated area, are still not fully described. This study aimed to evaluate the immediate effects of the ICMS on c-Fos cell immunoreactivity upon the stimulated area and the extent of this stimulation in S1, adjacent cortical areas, and also in the spinal cord of rats. It was observed that surrounding the microelectrode implant occurred a lower immunoreactivity extending to $$150{-}200\ \upmu $$ 150 - 200 μ m $$^{2}$$ 2 , however, there was no statistical significance to right and left directions (X $$^{2}$$ 2 (4) = 5.00, p = 0.29; X $$^{2}$$ 2 (4) = 6.33, p = 0.18). It was followed by a higher number of c-Fos immunoreactive cells between $$250{-}1000\ \upmu $$ 250 - 1000 μ m from the microelectrode track at the mediolateral directions, being statistically significant to $$500\ \upmu $$ 500 μ m at the rostroventral direction (F(2, 6) = 6.57, p = 0.031). Despite the qualitative differences in the number of immunoreactive cells, no statistically significant differences were observed to M1, S2, and spinal cord areas. This study corroborates with findings of previous research relative to the extent of neuronal activity and immunoreactivity after ICMS, adding that similar patterns of cortical immunoreactivity are seen in non-anesthetized stimulated animals.

A brain-machine interface (BMI) can be defined as a system that translates the brain activity patterns of a user into messages or commands for an interactive application. For patients with neurodegenerative diseases, who lost the ability to communicate during the progression of the disease, a BMI could be the only remaining possibility to interact with the environment. Event-related potentials (ERPs), especially the P300 component, are commonly used as control signal for these systems. The P300 component is elicited by rare stimuli amid a stream of frequent standard stimuli, such as in oddball tasks and can be influenced by several parameters related the stimulation, biological and psychological factors. The literature shows inconclusive results for the influence of frequency and channel of stimulation in the P300 component and the effect of these parameters on BMI. The goal of this study was to evaluate the impact of the stimulation frequency to find out if the same pattern of stimuli can be used for different subjects to promote similar ERPs. The experimental procedure consisted of the presentation of five mono target frequencies at the two channels of the headphone. The amplitude and latency of P300 was analyzed. The results indicate distinct individual responses and, therefore, the responses of different subjects should be properly evaluated before considering the use of auditory oddball paradigms for BMI interaction so that better performances and Information Transfer Rates can be achieved.

The development of highly sophisticated prosthetic hands is a long-sought goal for biomedical engineers. Overall improvements in hand design and control via myoelectric signals (EMG) allowed the development of devices with more degrees of freedom and higher capabilities. While the motor aspects of prosthetic hands have greatly evolved, there is room for improvements in their sensory aspects. Incorporating tactile sensors into the robotic fingers should improve the overall control of the hand, providing more safety when manipulating objects. Despite the many tactile sensors presented in the literature, there is a need for more flexible and higher-density tactile sensors. In this paper, we present the design of a novel neuromorphic tactile sensor for prosthetic hands. The sensor is composed by a photodiode array and light-emitting diodes (LEDs) embedded into a soft elastomer material. Forces applied to this artificial skin causes deformation of the elastomer, changing the distribution of light over the photodiodes, generating the tactile signal. We also follow a neuromorphic approach by converting such signals into spikes that mimic the behavior of Merkel Cells present in the glabrous skin. These mechanoreceptors are slow-adapting and encode static forces applied over the skin. The proposed tactile sensor is promising and can be incorporated to prosthetic hands to improve their dexterity in a biomimetic manner.

Event-based cameras are devices that can be the key to solving various robotics challenges. However, unlike the Computer Vision field, research in Neuromorphic Vision does not have enough data for algorithms to be tested, evaluated, and compared to guarantee progress in the development of robust and competitive solutions. In this way, we propose the development of a framework that converts information recorded by standard RGB cameras into neuromorphic information. Using this framework, we created neuromorphic recordings from videos used in Computer Vision datasets to test and evaluate our tracking algorithm in neuromorphic recordings. We obtained an average accuracy of 95.38% in tracking the information of the five videos selected in this work.

The classification of objects is a field very well explored by Computer Vision and has achieved excellent results over the last decade. The sophistication of biological systems has led us to the development of bioinspired technologies through Neuromorphic Engineering that proposes to develop robotic systems with operation inspired by the physiological processes found in nature. Seeking to combine the high speed of information processing, with the low dimensionality of the data and a reduced computational cost, we combine a neuromorphic vision sensor (DVS128) with a Convolutional Neural Network (CNN) to classify images of nine different objects. Our deep learning model achieved 75.31% accuracy when performing network validation using the holdout method.

Numerous neuromodulation techniques have been developed due to the importance of understanding functional neuroanatomy and deep brain circuits. This study aims to contribute to the understanding and innovation of the focused and non-invasive transcranial ultrasonic neuromodulation technique. Simulations were made to map the acoustic and the volume rate of heat deposition generated from the interaction of the ultrasonic waves with the biological tissue mimicked by a phantom built from an image of RM T1. The results of the simulations showed the possibility of ultrasound to reach deep brain targets through the skull without generating a considerable high heat deposition in the scalp, considering a risk for the patient. Therefore, the focused transcranial ultrasound is a viable method for neuromodulation in animals and humans.

In the last years, several works have searched better ways to perform upper-limb prosthesis control. However, current prosthesis control methods are still far from achieving the human limb features, like controlling many degrees of freedom mechanically. Moreover, the complexity of prosthesis control increases the user’s cognitive load, which decreases its usability and user satisfaction rates. Therefore, it is necessary to enhance upper-limb prosthesis control systems for facilitating their control. This work presents an alternative method, which works with the neuromorphic vision to automatize both wrist rotation and grasp selection, according to object orientation and shape.

Stroke is a neurological syndrome that may affect severely lower-limb movements and the normal gait. The complete or partial restoration may be achieved through alternative rehabilitation therapies, such as Motor Imagery (MI)-based Brain Computer Interfaces (BCIs). Although these systems have shown promising results on post-stroke patients with severe disability, their performance recognizing MI may be reduced for people executing MI tasks with high difficult or producing weak brain activation. This study presents a proposal to improve the calibration stage of a low-cost electroencephalographic (EEG) based MI BCI with pedal end-effector, which integrally aims to activate continuously the central and peripheral mechanisms related to lower-limbs, and obtain the best feature vectors for MI recognition. This setup enables users to perform pedaling MI and receive passive pedaling into a Calibration phase. Consequently users can produce related EEG signals useful to obtain those more discriminant MI feature vectors through a probability analysis combining patterns from pedaling MI and passive pedaling. Here, Riemannian geometry and Common Spatials Patterns (CSP) for feature extraction were used independently or combined in our approach. Preliminary results show that the proposed method may improve the BCI performance. For healthy subjects, the approach using CSP achieved accuracy (ACC) up to 98.43%, whereas for PS1 and PS2 obtained ACC of 71.07% and 79.24%, respectively. However, Riemannian geometry plus CSP using LDA reached better results for healthy subjects and patients (mean ACC of 73.84%).

Transcranial magnetic stimulation (TMS) is a noninvasive technique of brain stimulation that has been widely used in both cognitive function studies and clinical applications. However, the biophysical mechanisms by which TMS activates cortical neurons and networks are still poorly understood. The present work aimed to create a computational model of the neuronal effects of single-pulse TMS combining compartmental models of neurons and a subject-specific electric field solution. The model consists of neurons of cortical layers L2/3 and L5, transformed to conform to cortical curvature and subjected to extracellular quasipotentials following a monophasic current waveform. First, excitation thresholds and sites of action potential initiation are determined through simulation of membrane dynamics with neurons being synaptically isolated, then epidural response is simulated by connecting them in a feedforward network. Excitation occurred at morphological discontinuities such as axon terminals, and thresholds were mostly correlated with total electric field magnitude instead of the component normal to cortex. Coil orientations perpendicular to central sulcus presented lowest thresholds, with L5 neurons, in general, being more easily excitable than L2/3. The simulated epidural response of the network presented amplitude and duration in accord with experimental recordings, supporting the hypothesis of transsynaptic activation, with the time of propagation of action potentials in L2/3 axonal arbors suggesting a role in latency of I-waves. By incorporating neuroanatomical factors to a neuronal network, the current model offers a computational framework for exploring TMS parameters and advancing the personalized use of neurostimulation.

The objective of the present work is to offer an educational strategy targeting biomedical engineering/physics students focusing on the calculation of isotope concentrations and activities in radioactive decay chains, which is capable of demonstrating the behavior of these isotopes over time, by using an iterative process and basic mathematical operations. The computational modeling of the radioactive decay problem by solving ordinary differential equation systems using the Runge-Kutta Fourth Order numerical method is treated. The adopted physical and mathematical models are shown, as well as their computational routine.

The present study aimed to evaluate the effects of PBMT by LED on chondrocyte culture derived from articular cartilage of rats. All cell culture procedures were performed under stringent aseptic conditions in a biological safety cabinet. For this, the chondrocytes were extracted from the femoral articular cartilage of rats using 0.25% type I collagenase. After extraction, the cells were seeded at 5.104 cells and divided into 4 groups: Control (chondrocytes that did not receive PBMT); PBMT 70 mW (chondrocytes that received PBMT with a power of 70 mW); PBMT 150 mW (chondrocytes that received PBMT with a power of 150 mW); PBMT 300 mW (chondrocytes that received PBMT with a power of 300 mW). After 12 h of the cells being seeded, PBMT by LED (850 nm) was started and performed every 24 h, totaling 3 sessions. After this period, the viability and cell proliferation were analyzed. The results showed that all experimental groups were able to maintain cell viability. However, when cell proliferation was evaluated, only the 150 mW PBMT group was able to increase chondrocyte proliferation. In addition, the PBMT 70 mW and 300 mW groups presented lower cell proliferation when compared to the control group. Thus, it can be suggested that PBMT by LED induced a dose response effect and 150 mW power was able to maintain cell viability and proliferation.

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CM) are a promising experimental model of human myocardium for drug development and studies on cardiac pathophysiology, although their immature phenotype may limit their application. This study aimed at characterizing this model regarding Ca2+ transport by systems involved in cardiac relaxation. Ca2+ transients were recorded under different conditions of selective inhibition of these systems in hiPSC-CM from different batches, cultivated for different periods. The results indicate: (a) a pattern of interaction among Ca2+ transporters similar to that previously seen in neonatal rat myocardium, i.e., a greater impact of inhibiting the Na+-Ca2+ exchanger than impairing sarcoplasmic reticulum Ca2+ accumulation; (b) prolonging hiPSC-CM culture from 2 to 3 weeks did not result in further maturation of Ca2+ transport; (c) although data are comparable in cells from the same batch, the significant interbatch variation observed indicates the need of sampling several batches for reliable results and conclusions.

The development of Point Of Care (POC) systems for applications in biorecognition has motivated research on sensor platforms in which their electrochemical responses can be obtained without the use of redox probes. This paper describes the design and characterization of a film is composed by conductive polymers, nanoparticles and special organic salts. The platform consists of a film of Polianiline, Fulerene C60 and TCNQ, produced on the surface of a glassy carbon electrode and deposited using the drop-casting technique. For the characterization, the electrochemical cyclic voltammetry technique was used. In addition to the voltammogram profile, the reversibility of the platform was analyzed the anodic and cathodic peak current as a function of the scanning speed and its stability. The results demonstrate that produced platform presents significant increase in electron transfer and good electrochemical stability. The main characteristic of the produced platform is that they were tests electrochemical performed without the presence of a redox probe, indicating that all the electron transfer is conducted by the conductive characteristics of the film which was produced and occurrence and because the species generated on the surface the electrode. This represents the initial stage in the development of POC biosensors.

Obesity is a health problem known to increase the morbidity and mortality of individuals. Although widely used, body mass index is not considered a good parameter to assess harmful levels of body fat, since is not a good predictor of mortality. Several new methods have been proposed over the years, such as the waist-to-hip radio. Nevertheless, the predictive ability of this method is still inconclusive. This study presents two new evaluation methods (bioelectrical impedance and dual energy x-ray) and assesses the accuracy of both. We evaluated 30 obese patients. The measurements were taken in the morning after a minimum period of 4 h of fasting, with an interval of 10 min between assessments. There was an improvement in the evaluative capacity of BIA in relation to DXA, when compared to previous studies. This led to an equivalence in the evaluative capacity of both formats for assessing body composition.

This paper has two main objectives. The first one is to present a new dynamic model that describes, with adequate precision, the temporal behavior of the coronavirus epidemic that currently occurs in Brazil. Every day, the number of new infections provided by the Brazilian Ministry of Health is taken into account. Thus, an assessment of the impact of social behavior on the evolution of the epidemic can also be made. The second objective is to analyze the need to develop a computational system, capable of simulating—with the Monte Carlo method—the dynamic behavior of epidemics allowing each individual to move through locations with different population densities.

Endodontic treatments provide high success rates, due to technical, scientific and biological evolution. However, periapical lesions that do not regress after endodontic treatment, which forms exudate, can be considered a persistent disease and very complex clinical measures must be taken to resolve it. Therefore, with the failure of endodontic therapy, an excellent tool can be used to solve this problem, which is the use of parendodontic surgery. Among the procedures used in this surgery, there is apicectomy, which consists of removing the apical portion of the dental element followed of curettage of pathological tissue. Thus, this study aimed to assess apicectomy by means of follow-up exams, such as digital and computerized radiography and tomography, in recurrent periapical disease after failure of endodontic treatment in a case study. The clinical case had a retrograde filling with the addition of mineral trioxide. In this work, the relevance of parendodontic surgery was verified in the case which the good quality conventional endodontic treatment cannot promote the repair. It can be seen that imaging resources, such as Cone-Beam Computed Tomography, allowed an image with greater quality and effectiveness because of its three-dimensional character, resulting in better evidence of bone repair and demonstrating the success of parendodontic surgical treatment.

In this paper we present the design and development of an didactic ECG signal generator to be implemented along with laboratory practices of an undergraduate basic electronics course, offered at FEEC/UNICAMP. The prototype produces ECG signals employing fundamental electrical circuits and concepts incorporated in the vast majority of medical equipment. It is evident, in the course of one of the greatest world health crisis in recent decades, the need for training qualified professionals (biomedical engineers) for the development of medical equipment. A good biomedical engineer does need to understand basic electronics, the human physiology and be able to design and construct simple and efficient electronics circuits often found in electromedical equipment. Our students had to cope with all expected program of the course content involving feedback, linear voltage regulators, operational amplifier topologies active filters, theoretical and practical aspects on signal amplification, digital-to-analog (D/A) and analog-to-digital (A/D) circuits and biological signal acquisition and processing. Although this paper shows only D/A circuits to construct a simple ECG signal generator, several other circuits can be built with the same methodology. The students have given us strong positive feedback. We noted very good results, both in the technical and motivational aspects with the students showing enthusiasm with great engagement and participation. We conclude that teaching electronics with practical problems is the best way to engage the students in the learning process.

The automated classification of speech emotions is a potential candidate for clinical applications or even for educational purposes in the training of students. A description of procedures to evaluate emotional states from voice recordings in different environments is presented, together with extraction and the selection of features such as Fundamental Frequency, energy, formants and Mel-Frequency Cepstrum Coefficients (MFCC). For comparison purposes three speech corpus, one made by actors using the German language, and two made by inducing emotions in English and Brazilian Portuguese. A number of 208 features were extracted, this number was reduced using selection and emotion classification was performed by the use of a Support Vector Machine algorithm. The objective of this work was to compare results from different databases based on the classification of emotions with supervised learning algorithms.

Patients hospitalized in an intensive care setting are considered critical patients. Thus, they are often dependent on resources for maintaining life that make it impossible for the individual to move, leading to muscle loss. This loss already occurs in the first days of hospitalization and takes a longer recovery time, even after hospital discharge. That is why it is relevant to study methods of monitoring and diagnosing muscle weakness acquired in the Intensive Care Unit (ICU). The objective of this study is to perform a bibliometric study to verify the protocols and parameters used by portable ultrasonography (US) in the evaluation of loss of muscle mass in individuals admitted to the intensive care setting. A bibliometric study was carried out in which 22 articles formed the research portfolio. The results showed that most of the studies were intervention (with different protocols for applying the US). We also found that ultrasound has been compared to other diagnostic methods, obtaining the best correlation with biopsy. For the diagnosis, the musculature of the lower limbs is recommended, mainly the rectus femoris muscle, for being more likely to atrophy due to disuse. In addition to the US, other methods of monitoring muscle loss were used, such as dynamometry and the Medical Research Council (MRC) scale, but these are restricted to being applied only to awake patients who can understand instructions. As a conclusion, the use of ultrasound is identified as a safe method with good intraobserver and interobserver reliability and that there is a gap regarding the therapeutic intervention for the treatment of muscle weakness acquired in the ICU.

Quality of life (QOL) is how the individual perceives himself as having an impact on his physical-emotional integrity, functional capacity, and self-esteem. Quality of life assessment tools can be generic or specific. Generics evaluate various aspects of quality of life and health status, and can be useful for patients, regardless of disease or condition, and can also be used for healthy individuals. The Medical questionnaire Outcomes Study 36 (SF-36) is one of the main instruments used to assess the health-related quality of life. This study aimed to develop the first application software (APP) for assessing the quality of life in Portuguese. This is an experimental study, of analytical, observational, and transversal nature that seeks associations or correlations between variables of interest. The application was developed on the Unity Engine to facilitate port for Android and its graphical interface. The Sarcvida app contemplates the SF-36 questionnaire and the SARC-F+CC. The application has undergone structural and functional tests and the next step is the evaluation of the app by health professionals. Sarcvida app is composed of SF-36 QOL questionnaire, SARC-F+CC, and D-score. The application proved to be functional, corresponding to initial research expectations for the project. The app presented usability and functionality for the evaluation of QOL in the tests to which it has been submitted so far. In Brazil there are no applications composed of SF-36 QOL questionnaire, SARC-F+CC, and the D-score, therefore, this study is innovative, presenting the first Portuguese version available in the app. Besides, mobile technology developed here is a tool to help monitor patients by contributing health professionals in possible interventions for health promotion.

In recent years, technology-based studies have surfaced due to the growing interest in the global problem of antibiotic resistance, especially in the bioinformatics field applied to metagenomics, which is able to represent the microorganism and its associated genes in terms of antibiotic resistance. This paper aims to present a novel approach to categorize antibiotic-resistant genes data based on metagenomic databases through an analysis with histogram-based signal processing. The preliminary results show that the approach is effective to identify antibiotic-resistant genes and has a relatively low computational cost.

The species Copaifera reticulata Ducke, popularly known as copaiba or wood of oil-resin occurs in Acre. It has a high medicinal potential due to the chemical properties present in its oil-resin. However, intensive wood exploitation and inadequate oil extraction threaten the continuity of the species, and the production of seedlings in nurseries are required. In this way, this work evaluated the impact of ultrasonography in the emergence and initial growth of C. reticulata seedlings. The emergence of seedlings was observed through the parameters Emergency Percentage (EP), Emergency Speed Index (ESI) and Average Emergency Time (AET), and initial growth by Aerial Part (H) and Root of the Seedlings (RS), Diameter at Height root-stem transition zone (DC), and Dry Mass of the Aerial Part (MSPA), Root Dry Mass (MSR) and Total Dry Mass (TDM). The following groups were used: control group (water immersion), treatments T1, T2 and T3 with 1 MHz of frequency and intensity following the order 0.5; 1.0 and 1.5 W/cm2. Groups T4, T5 and T6 with a frequency of 3 MHz, and with intensity of 0.5; 1.0 and 1.5 W/cm2, respectively. All with application for 5 min. The highest values of EP and ESI were observed in T1, T3 which, in turn presented the smallest AET. The best development was observed for H and RS in T5. It is inferred that the use of ultrasound benefited the emergence of C. reticulata seedlings, and also initial growth, however, the use of ultrasonic waves with intensity above 1.0 W/cm2 for 5 min has demonstrated not to be as advantageous as the use of smaller intensities.

The global situation caused by a coronavirus in 2020 has become an unprecedented health crisis. Since 1918, during the Spanish flu, Brazilian society haven’t seen a pandemic disease. Among the many individuals exposed to the virus, health care professionals are essential workers who fight the disease. However, due to the lack of previous investments in the public health sector in Brazil, several obstacles are evident, such as the reduced number of Personal Protective Equipment (PPE) available for healthcare professionals who have direct contact with those affected by the disease. Therefore, undergraduate students and professors from UFPA (Universidade Federal do Pará—Federal University of Pará) Biomedical Engineering program course mobilized to create solutions to this problem through the study and production of a low-cost face shield model, which proved to be essential in helping professionals, in addition to engaging several students in the social causes. Similar initiatives like this took place in states in southeastern Brazil, through the making of PPE in 3D printers from PLA (polylactic acid) or ABS (Acrylonitrile Butadiene Styrene) filaments, which can take hours to be ready. Therefore, the present study presents a handmade model to promote higher cost–benefit and shorter manufacturing time. To measure how this PPE proposed here affected the daily work of these professionals, this study performed a feedback form focused on the professionals who used the handmade model. Also, a comparison between the 3D printed versus the handmade model was done. The study showed that 69.5% of the respondents, which were professionals working in the health field, felt more protected with the handmade face shield. Finally, for this research, it is possible to say that the handmade faceshields have proven to be effective, providing confidence when used by the research participants.

SARS-CoV2-related infections have drawn the researchers’ attention to skin lesions. The motivation and purpose to present the cutaneous manifestations related to COVID-19 caused by SARS-CoV2 and the prolonged use of Personal Protective Equipment (PPE) by health professionals. The aim of the study is performed a systematic review of studies and official documents were carried out, in order to explore and synthesize the evidences and recommendations about the cutaneous manifestations related to SARS-CoV2 and the use of PPE. An integrative literature review was carried out with a search on the VHL library (LILACS, MEDLINE, SciELO). Articles from the period 2019 to june 2020 were included. In the results, 37 references were included, 10 original articles, 03 literature reviews and 24 other types of scientific publications. The conclusions demonstrated that the skin manifestations related to COVID-19 can be directly associated with the new SARS-CoV2, however it is necessary to have more conclusive studies. Skin lesions that have affected patients and frontline health professionals who need special care with the use of PPE.

Biosensor development and biorecognition systems such as Point-of-care (POC) devices, have been studied and applied in sensors platforms to help the diagnosis of some diseases. This work presents the construction of a cost-effective POC device for sensitive detection with the aid of a swab graphite electrode and a carbon nanotubes (CNT) and chitosan (CHIT) film characterization. This unique and simple electrode design allows better contact with the target analyte without additional preparations. Cyclic voltammetry tests and dip coating techniques were performed. The results show a significant increase in the current area measurement of the graphite surface which contributes as an economical alternative for the manufacture of biosensors.

Breast engorgement (BE) is defined as the distension and swelling present in the breasts, observed at the beginning of lactation, causing vascular dilation, alveolar distention, and compression of the ducts. Therapeutic ultrasound (UST) is a resource that produces thermal effects, increasing the permeability of the cell membrane and its transport gradients, reducing the viscosity of fluids, promoting relief of the symptoms of breast engorgement. This research used thermography to assess temperature changes by thermographic images before and 24 h after application of the UST to BE. The study consisted of a randomized clinical trial, with 12 women, who were divided into the following groups: Control (n = 4), UST 1 MHz (n = 4) and UST 3 MHz (n = 4). The UST is a Sonopulse III model (IBRAMED), and configured in: continuous mode, frequency of 1 MHz, effective intensity of 2 W/cm2 for G1 and continuous mode, frequency of 3 MHz, effective intensity of 2 W/cm2 for G2, lasting 5 min in each quadrant. The images were recorded using an infrared camera, model E6 (Flir Systems Inc., Wilconville, USA), and subsequently analyzed using the Flir tools program. It was observed that the use of 1-MHz ultrasound demonstrated a significant reduction in temperature in the breast tissue 24 h after application, with no evidence of hot spots on the surface, inferring a reduction in the inflammatory process produced by the BE. There is no significant difference between temperature before and 24 h after treatment with 3-MHz UST application and Control Group.

Therapeutic ultrasound (UST) has thermal biological effects produced by mechanical waves that vibrate continuously to reach temperatures between 40 and 45 °C for about 5–10 min to produce beneficial physiological changes. Several researches with the objective of studying the field and the thermal effect of UST in metallic implants, were carried out in phantoms, animals in vivo and ex vivo. This work aimed to investigate the effects of therapeutic ultrasound on the muscle/bone tissue-swine interface (Sus scrofa domesticus) with metallic implant through thermography and histopathology. After placing the metallic implant, the piece was sutured, and placed in a controlled thermal bath at 36 °C and irradiated with therapeutic ultrasound for 10 min, at a frequency of 1 MHz, intensity 2 W/cm2, stationary mode. The tissue temperature was measured before and after the application of therapeutic ultrasound. The thermographic image of the piece after the ultrasound application clearly shows the points of greatest heating were outside the metal region, in the lateral musculature with an average of around 49.1 °C. The muscular region above the metallic part had an average temperature of 46.3 °C while the metallic implant had an average temperature of 40.7 °C. Histopathology shows some cell injuries in the skeletal striated fibers (peroneal muscle) in an area where there was a metallic implant. The causes of cell injuries have not been clarified in the current study. It was not possible to diagnose whether the use of UST contributed to the formation of physical cellular lesions found in the fibers.

Infrared thermography is an imaging technique applied in studies to aid in the diagnosis of several types of cancer, including thyroid cancer. Tumors generate changes (anatomical and vascular) that are shown in thermal images. This paper shows the creation of semiautomatic segmentation software to assist in the diagnosis of tumors in dynamic thermograms. For the beginning of the analysis, the software allows the creation of a project using the text files exported by the camera and interpreting them as a temperature matrix. Then, it allows to change the scale of the displayed image and choose the color palette used in the temperature conversion for color. The FloodFill algorithm delimits the regions of interest (area with tumor and healthy) when the user positions the cursor (seed expansion) on the tumor, and defines the threshold of difference. The extraction of data in the segmented region provides: the temperatures (maximum, minimum and average); the number of pixels involved in the segmentation area; allows the export of the data in a .cvs file (compatible with other programs, such as excel); and provides a graph with the thermal difference between the two areas analyzed (healthy and with tumor). The application of the software has been demonstrated in two thyroid tumors, one malignant and one benign. In the malignant one, it is possible to observe higher temperatures in the tumors compared to the healthy regions during the rewarming period after cold stress, different thermal behavior between benign and malignant tumors, as well as a larger number of pixels in the segmented area of the malignant tumor, when compared to benign. It is expected that the information extracted from each tumor (and surrounding healthy areas) can be useful for the clinical diagnosis in the correct indication of biopsies considering that the thermographic image contains information that goes beyond a simple temperature measurement.

OSL and TL are luminescent techniques used for individual monitoring for the assessment of doses. Calcium fluoride (CaF2) detectors are successfully applied for personal dosimetry combined TL technique. Studies published in the last years highlight the dosimetric properties of this material with the OSL technique. Considering the advantages of OSL in personal dosimetry and luminescent properties of CaF2 detectors, in this work we developed an algorithm method for evaluation of operational quantity Hp(10) with CaF2 detectors used by workers exposed to radiation energy range find in radiodiagnostic services. A blind test with CaF2 detectors was performed. The analysis of Hp(10) results using the trumpet curve criteria was performed for both setups of energy range of x-ray photon beam. In both blind tests, the criteria of the trumpet curve were fulfilled, demonstrating the applicability of CaF2 detectors with the OSL technique, as the developed algorithm, in radiation monitoring for workers at diagnostic imaging services.